Podcasts about Rahul

This episode featured a conversation with Rahul Sonpimple, founder of the All-India Independent Scheduled Castes Association. Our conversation began with Rahul's conception of Indian history and the place of anti-caste struggle within it. We delved further into Rahul's own understanding of “anti-caste” as deeply rooted in Ambedkar's own argument about the necessity of force in emancipatory social transformation. Rahul was especially forthright about the political cost of elevating meekness as a moral condition, a choice that he associates with the rise of a Dalit middle class focused primarily on securing its own representational authority. This took us to a discussion of the need for an independent and consolidated Dalit politics rooted in the lives of the Dalit poor with sufficient leverage to negotiate terms with the state. The last part of the episode focused on Rahul's critique of both Ambedkarites and Indian Marxists for their disregard of caste as a material question. He spoke at particular length about the failure of Indian Marxists to advance a materalist critique of caste and how their analytical separation of caste and class has played into the hands of the Hindu Right. We ended the episode with Rahul laying out his own definition of Ambedkarism as a material and spiritual politics that recognizes the Dalit poor as a revolutionary class with the potential to rebuild society. Read the transcript here Guest Rahul Sonpimple is author and founder of the All-India Independent Scheduled Castes Association. References B.R. Ambedkar, The Buddha and his Dhamma, 1957. B.R. Ambedkar, Small Holdings in India and their Remedies, 1918. B.R. Ambedkar, Buddha or Karl Marx, 1956. B.R. Ambedkar, “Mr. Russell and the Reconstruction of Society,” 1916. Rahul Sonpimple, “Against Hindu Rashtra: Ambedkar's Buddhist Rashtra as Nation,” The Ambedkarian Chronicle, May 4, 2026. Rahul Sonpimple, “Remembering Babasaheb Ambedkar: The Unfinished Task of Burying Manu,” The Ambedkarian Chronicle, April 14, 2026. Rahul Sonpimple, “Kanshi Ram Sahab: Beyond Bureaucratic Dalit Passivity,” The Ambedkarian Chronicle, March 15, 2026. Rahul Sonpimple, “Spontaneity in Ambedkar: Beyond the Passivity of Popular Dalit Discourse,” The Ambedkarian Chronicle, April 16, 2025. Rahul Sonpimple, “The End of Independent Ambedkarite Dalit Politics?” Round Table India, July 12, 2024. Rahul Sonpimple, “Dalit conversions: An act of rebellion against caste supremacy,” Al Jazeera, 14 June 2018. Himsa and ahimsa are foundational ethical concepts in Buddhism. Himsa refers to injury, harm, or violence and ahimsa to non-harming, non-violence, or compassion. Ambedkar critiqued extreme, blanket doctrines of ahimsa as unworkable and often hypocritical. Chokhamela was a saint-poet from Maharashtra, India who belonged to the Mahar caste and was a devotee of Vitthala. Bhakt: devotee Vitthala: Hindu deity worshipped mainly in the states of Maharashtra and Karnataka as an avatar of Vishnu. Kabir and Ravidas: medieval poet-saints who were part of the Bhakti movement (7th-17th century), which emphasized devotion to a personal god, rather than rituals and scriptural knowledge, as the path to spiritual liberation. Samata Sainik Dal: a social organization founded by B. R. Ambedkar in 1927 with the objective of safeguarding the rights of all oppressed sections of Indian society. Bhima Koregaon: a village in Maharashtra that was the site of an 1818 battle between the army of Peshwa Baji Rao II and an East India Company force comprised mainly of Mahars, a Dalit caste. This battle has attained legendary status for Dalits who view it as a victory of Mahars over the Brahminical Peshwas. Baniya: refers to mercantile castes primarily from the states of Rajasthan and Gujarat. Kanshi Ram: Indian social reformer and politician who founded the All India Backwards and Minorities Communities Employees' Federation (BAMCEF) in 1971 and the Bahujan Samaj Party in 1984. Jogendra Nath Mandal: Bengali politician and Dalit leader who held the law portfolio in the 1946-47 Interim Government of India and served as the Minister of Law and Labor in Pakistan from 1947-50. Rajah: M.C. Rajah was a Tamil politician and Dalit leader who served on the Madras Legislative Council in the 1920s and founded the All India Depressed Classes Association in 1925. Kamble: B.C. Kamble was a Marathi politician and Dalit leader who led the Republican Party of India for decades. BAMCEF: All India Backwards and Minorities Communities Employees' Federation UGC Bill: officially the University Grants Commission (Promotion of Equity in Higher Education Institutions) Regulations, 2026, is a set of regulations aimed at ending discrimination against marginalized communities in higher education. Following widespread protests and a public interest litigation (PIL), the Supreme Court of India stayed the regulations in January 2026. Bhagwa kapda: saffron clothing Scheduled Caste Federation: a political organization founded in 1942 by Dr. B. R. Ambedkar dedicated to advocating for the rights and political self-representation of the Dalit community. Republican Party of India: a political party established by Dr. B. R. Ambedkar in 1956. PESA: Panchayats Extension to Scheduled Areas (PESA) Act, 1996 is a landmark legislation enacted by the Government of India to ensure self-governance for tribal communities living in Fifth Schedule Areas. Manusmriti: a text that served as a foundational legal and societal framework in ancient India. EWS: refers to the Economically Weaker Section, a government classification referring to those within the unreserved (general) category eligible for a 10% quota in government jobs and educational admissions. Karan Johar: an Indian filmmaker, producer and television personality. Dharavi: a residential area in Mumbai (Bombay) considered one of the world's largest slums. Adani: Gautam Adani is an Indian billionaire and chairperson of the multinational conglomerate, the Adani Group. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

PM Modi Praised Skyroot Aerospace | India's Startup Revolution | PM Modi Roasts Rahul

This episode featured a conversation with Rahul Sonpimple, founder of the All-India Independent Scheduled Castes Association. Our conversation began with Rahul's conception of Indian history and the place of anti-caste struggle within it. We delved further into Rahul's own understanding of “anti-caste” as deeply rooted in Ambedkar's own argument about the necessity of force in emancipatory social transformation. Rahul was especially forthright about the political cost of elevating meekness as a moral condition, a choice that he associates with the rise of a Dalit middle class focused primarily on securing its own representational authority. This took us to a discussion of the need for an independent and consolidated Dalit politics rooted in the lives of the Dalit poor with sufficient leverage to negotiate terms with the state. The last part of the episode focused on Rahul's critique of both Ambedkarites and Indian Marxists for their disregard of caste as a material question. He spoke at particular length about the failure of Indian Marxists to advance a materalist critique of caste and how their analytical separation of caste and class has played into the hands of the Hindu Right. We ended the episode with Rahul laying out his own definition of Ambedkarism as a material and spiritual politics that recognizes the Dalit poor as a revolutionary class with the potential to rebuild society. Read the transcript here Guest Rahul Sonpimple is author and founder of the All-India Independent Scheduled Castes Association. References B.R. Ambedkar, The Buddha and his Dhamma, 1957. B.R. Ambedkar, Small Holdings in India and their Remedies, 1918. B.R. Ambedkar, Buddha or Karl Marx, 1956. B.R. Ambedkar, “Mr. Russell and the Reconstruction of Society,” 1916. Rahul Sonpimple, “Against Hindu Rashtra: Ambedkar's Buddhist Rashtra as Nation,” The Ambedkarian Chronicle, May 4, 2026. Rahul Sonpimple, “Remembering Babasaheb Ambedkar: The Unfinished Task of Burying Manu,” The Ambedkarian Chronicle, April 14, 2026. Rahul Sonpimple, “Kanshi Ram Sahab: Beyond Bureaucratic Dalit Passivity,” The Ambedkarian Chronicle, March 15, 2026. Rahul Sonpimple, “Spontaneity in Ambedkar: Beyond the Passivity of Popular Dalit Discourse,” The Ambedkarian Chronicle, April 16, 2025. Rahul Sonpimple, “The End of Independent Ambedkarite Dalit Politics?” Round Table India, July 12, 2024. Rahul Sonpimple, “Dalit conversions: An act of rebellion against caste supremacy,” Al Jazeera, 14 June 2018. Himsa and ahimsa are foundational ethical concepts in Buddhism. Himsa refers to injury, harm, or violence and ahimsa to non-harming, non-violence, or compassion. Ambedkar critiqued extreme, blanket doctrines of ahimsa as unworkable and often hypocritical. Chokhamela was a saint-poet from Maharashtra, India who belonged to the Mahar caste and was a devotee of Vitthala. Bhakt: devotee Vitthala: Hindu deity worshipped mainly in the states of Maharashtra and Karnataka as an avatar of Vishnu. Kabir and Ravidas: medieval poet-saints who were part of the Bhakti movement (7th-17th century), which emphasized devotion to a personal god, rather than rituals and scriptural knowledge, as the path to spiritual liberation. Samata Sainik Dal: a social organization founded by B. R. Ambedkar in 1927 with the objective of safeguarding the rights of all oppressed sections of Indian society. Bhima Koregaon: a village in Maharashtra that was the site of an 1818 battle between the army of Peshwa Baji Rao II and an East India Company force comprised mainly of Mahars, a Dalit caste. This battle has attained legendary status for Dalits who view it as a victory of Mahars over the Brahminical Peshwas. Baniya: refers to mercantile castes primarily from the states of Rajasthan and Gujarat. Kanshi Ram: Indian social reformer and politician who founded the All India Backwards and Minorities Communities Employees' Federation (BAMCEF) in 1971 and the Bahujan Samaj Party in 1984. Jogendra Nath Mandal: Bengali politician and Dalit leader who held the law portfolio in the 1946-47 Interim Government of India and served as the Minister of Law and Labor in Pakistan from 1947-50. Rajah: M.C. Rajah was a Tamil politician and Dalit leader who served on the Madras Legislative Council in the 1920s and founded the All India Depressed Classes Association in 1925. Kamble: B.C. Kamble was a Marathi politician and Dalit leader who led the Republican Party of India for decades. BAMCEF: All India Backwards and Minorities Communities Employees' Federation UGC Bill: officially the University Grants Commission (Promotion of Equity in Higher Education Institutions) Regulations, 2026, is a set of regulations aimed at ending discrimination against marginalized communities in higher education. Following widespread protests and a public interest litigation (PIL), the Supreme Court of India stayed the regulations in January 2026. Bhagwa kapda: saffron clothing Scheduled Caste Federation: a political organization founded in 1942 by Dr. B. R. Ambedkar dedicated to advocating for the rights and political self-representation of the Dalit community. Republican Party of India: a political party established by Dr. B. R. Ambedkar in 1956. PESA: Panchayats Extension to Scheduled Areas (PESA) Act, 1996 is a landmark legislation enacted by the Government of India to ensure self-governance for tribal communities living in Fifth Schedule Areas. Manusmriti: a text that served as a foundational legal and societal framework in ancient India. EWS: refers to the Economically Weaker Section, a government classification referring to those within the unreserved (general) category eligible for a 10% quota in government jobs and educational admissions. Karan Johar: an Indian filmmaker, producer and television personality. Dharavi: a residential area in Mumbai (Bombay) considered one of the world's largest slums. Adani: Gautam Adani is an Indian billionaire and chairperson of the multinational conglomerate, the Adani Group. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/critical-theory

This episode featured a conversation with Rahul Sonpimple, founder of the All-India Independent Scheduled Castes Association. Our conversation began with Rahul's conception of Indian history and the place of anti-caste struggle within it. We delved further into Rahul's own understanding of “anti-caste” as deeply rooted in Ambedkar's own argument about the necessity of force in emancipatory social transformation. Rahul was especially forthright about the political cost of elevating meekness as a moral condition, a choice that he associates with the rise of a Dalit middle class focused primarily on securing its own representational authority. This took us to a discussion of the need for an independent and consolidated Dalit politics rooted in the lives of the Dalit poor with sufficient leverage to negotiate terms with the state. The last part of the episode focused on Rahul's critique of both Ambedkarites and Indian Marxists for their disregard of caste as a material question. He spoke at particular length about the failure of Indian Marxists to advance a materalist critique of caste and how their analytical separation of caste and class has played into the hands of the Hindu Right. We ended the episode with Rahul laying out his own definition of Ambedkarism as a material and spiritual politics that recognizes the Dalit poor as a revolutionary class with the potential to rebuild society. Read the transcript here Guest Rahul Sonpimple is author and founder of the All-India Independent Scheduled Castes Association. References B.R. Ambedkar, The Buddha and his Dhamma, 1957. B.R. Ambedkar, Small Holdings in India and their Remedies, 1918. B.R. Ambedkar, Buddha or Karl Marx, 1956. B.R. Ambedkar, “Mr. Russell and the Reconstruction of Society,” 1916. Rahul Sonpimple, “Against Hindu Rashtra: Ambedkar's Buddhist Rashtra as Nation,” The Ambedkarian Chronicle, May 4, 2026. Rahul Sonpimple, “Remembering Babasaheb Ambedkar: The Unfinished Task of Burying Manu,” The Ambedkarian Chronicle, April 14, 2026. Rahul Sonpimple, “Kanshi Ram Sahab: Beyond Bureaucratic Dalit Passivity,” The Ambedkarian Chronicle, March 15, 2026. Rahul Sonpimple, “Spontaneity in Ambedkar: Beyond the Passivity of Popular Dalit Discourse,” The Ambedkarian Chronicle, April 16, 2025. Rahul Sonpimple, “The End of Independent Ambedkarite Dalit Politics?” Round Table India, July 12, 2024. Rahul Sonpimple, “Dalit conversions: An act of rebellion against caste supremacy,” Al Jazeera, 14 June 2018. Himsa and ahimsa are foundational ethical concepts in Buddhism. Himsa refers to injury, harm, or violence and ahimsa to non-harming, non-violence, or compassion. Ambedkar critiqued extreme, blanket doctrines of ahimsa as unworkable and often hypocritical. Chokhamela was a saint-poet from Maharashtra, India who belonged to the Mahar caste and was a devotee of Vitthala. Bhakt: devotee Vitthala: Hindu deity worshipped mainly in the states of Maharashtra and Karnataka as an avatar of Vishnu. Kabir and Ravidas: medieval poet-saints who were part of the Bhakti movement (7th-17th century), which emphasized devotion to a personal god, rather than rituals and scriptural knowledge, as the path to spiritual liberation. Samata Sainik Dal: a social organization founded by B. R. Ambedkar in 1927 with the objective of safeguarding the rights of all oppressed sections of Indian society. Bhima Koregaon: a village in Maharashtra that was the site of an 1818 battle between the army of Peshwa Baji Rao II and an East India Company force comprised mainly of Mahars, a Dalit caste. This battle has attained legendary status for Dalits who view it as a victory of Mahars over the Brahminical Peshwas. Baniya: refers to mercantile castes primarily from the states of Rajasthan and Gujarat. Kanshi Ram: Indian social reformer and politician who founded the All India Backwards and Minorities Communities Employees' Federation (BAMCEF) in 1971 and the Bahujan Samaj Party in 1984. Jogendra Nath Mandal: Bengali politician and Dalit leader who held the law portfolio in the 1946-47 Interim Government of India and served as the Minister of Law and Labor in Pakistan from 1947-50. Rajah: M.C. Rajah was a Tamil politician and Dalit leader who served on the Madras Legislative Council in the 1920s and founded the All India Depressed Classes Association in 1925. Kamble: B.C. Kamble was a Marathi politician and Dalit leader who led the Republican Party of India for decades. BAMCEF: All India Backwards and Minorities Communities Employees' Federation UGC Bill: officially the University Grants Commission (Promotion of Equity in Higher Education Institutions) Regulations, 2026, is a set of regulations aimed at ending discrimination against marginalized communities in higher education. Following widespread protests and a public interest litigation (PIL), the Supreme Court of India stayed the regulations in January 2026. Bhagwa kapda: saffron clothing Scheduled Caste Federation: a political organization founded in 1942 by Dr. B. R. Ambedkar dedicated to advocating for the rights and political self-representation of the Dalit community. Republican Party of India: a political party established by Dr. B. R. Ambedkar in 1956. PESA: Panchayats Extension to Scheduled Areas (PESA) Act, 1996 is a landmark legislation enacted by the Government of India to ensure self-governance for tribal communities living in Fifth Schedule Areas. Manusmriti: a text that served as a foundational legal and societal framework in ancient India. EWS: refers to the Economically Weaker Section, a government classification referring to those within the unreserved (general) category eligible for a 10% quota in government jobs and educational admissions. Karan Johar: an Indian filmmaker, producer and television personality. Dharavi: a residential area in Mumbai (Bombay) considered one of the world's largest slums. Adani: Gautam Adani is an Indian billionaire and chairperson of the multinational conglomerate, the Adani Group. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/anthropology

This episode featured a conversation with Rahul Sonpimple, founder of the All-India Independent Scheduled Castes Association. Our conversation began with Rahul's conception of Indian history and the place of anti-caste struggle within it. We delved further into Rahul's own understanding of “anti-caste” as deeply rooted in Ambedkar's own argument about the necessity of force in emancipatory social transformation. Rahul was especially forthright about the political cost of elevating meekness as a moral condition, a choice that he associates with the rise of a Dalit middle class focused primarily on securing its own representational authority. This took us to a discussion of the need for an independent and consolidated Dalit politics rooted in the lives of the Dalit poor with sufficient leverage to negotiate terms with the state. The last part of the episode focused on Rahul's critique of both Ambedkarites and Indian Marxists for their disregard of caste as a material question. He spoke at particular length about the failure of Indian Marxists to advance a materalist critique of caste and how their analytical separation of caste and class has played into the hands of the Hindu Right. We ended the episode with Rahul laying out his own definition of Ambedkarism as a material and spiritual politics that recognizes the Dalit poor as a revolutionary class with the potential to rebuild society. Read the transcript here Guest Rahul Sonpimple is author and founder of the All-India Independent Scheduled Castes Association. References B.R. Ambedkar, The Buddha and his Dhamma, 1957. B.R. Ambedkar, Small Holdings in India and their Remedies, 1918. B.R. Ambedkar, Buddha or Karl Marx, 1956. B.R. Ambedkar, “Mr. Russell and the Reconstruction of Society,” 1916. Rahul Sonpimple, “Against Hindu Rashtra: Ambedkar's Buddhist Rashtra as Nation,” The Ambedkarian Chronicle, May 4, 2026. Rahul Sonpimple, “Remembering Babasaheb Ambedkar: The Unfinished Task of Burying Manu,” The Ambedkarian Chronicle, April 14, 2026. Rahul Sonpimple, “Kanshi Ram Sahab: Beyond Bureaucratic Dalit Passivity,” The Ambedkarian Chronicle, March 15, 2026. Rahul Sonpimple, “Spontaneity in Ambedkar: Beyond the Passivity of Popular Dalit Discourse,” The Ambedkarian Chronicle, April 16, 2025. Rahul Sonpimple, “The End of Independent Ambedkarite Dalit Politics?” Round Table India, July 12, 2024. Rahul Sonpimple, “Dalit conversions: An act of rebellion against caste supremacy,” Al Jazeera, 14 June 2018. Himsa and ahimsa are foundational ethical concepts in Buddhism. Himsa refers to injury, harm, or violence and ahimsa to non-harming, non-violence, or compassion. Ambedkar critiqued extreme, blanket doctrines of ahimsa as unworkable and often hypocritical. Chokhamela was a saint-poet from Maharashtra, India who belonged to the Mahar caste and was a devotee of Vitthala. Bhakt: devotee Vitthala: Hindu deity worshipped mainly in the states of Maharashtra and Karnataka as an avatar of Vishnu. Kabir and Ravidas: medieval poet-saints who were part of the Bhakti movement (7th-17th century), which emphasized devotion to a personal god, rather than rituals and scriptural knowledge, as the path to spiritual liberation. Samata Sainik Dal: a social organization founded by B. R. Ambedkar in 1927 with the objective of safeguarding the rights of all oppressed sections of Indian society. Bhima Koregaon: a village in Maharashtra that was the site of an 1818 battle between the army of Peshwa Baji Rao II and an East India Company force comprised mainly of Mahars, a Dalit caste. This battle has attained legendary status for Dalits who view it as a victory of Mahars over the Brahminical Peshwas. Baniya: refers to mercantile castes primarily from the states of Rajasthan and Gujarat. Kanshi Ram: Indian social reformer and politician who founded the All India Backwards and Minorities Communities Employees' Federation (BAMCEF) in 1971 and the Bahujan Samaj Party in 1984. Jogendra Nath Mandal: Bengali politician and Dalit leader who held the law portfolio in the 1946-47 Interim Government of India and served as the Minister of Law and Labor in Pakistan from 1947-50. Rajah: M.C. Rajah was a Tamil politician and Dalit leader who served on the Madras Legislative Council in the 1920s and founded the All India Depressed Classes Association in 1925. Kamble: B.C. Kamble was a Marathi politician and Dalit leader who led the Republican Party of India for decades. BAMCEF: All India Backwards and Minorities Communities Employees' Federation UGC Bill: officially the University Grants Commission (Promotion of Equity in Higher Education Institutions) Regulations, 2026, is a set of regulations aimed at ending discrimination against marginalized communities in higher education. Following widespread protests and a public interest litigation (PIL), the Supreme Court of India stayed the regulations in January 2026. Bhagwa kapda: saffron clothing Scheduled Caste Federation: a political organization founded in 1942 by Dr. B. R. Ambedkar dedicated to advocating for the rights and political self-representation of the Dalit community. Republican Party of India: a political party established by Dr. B. R. Ambedkar in 1956. PESA: Panchayats Extension to Scheduled Areas (PESA) Act, 1996 is a landmark legislation enacted by the Government of India to ensure self-governance for tribal communities living in Fifth Schedule Areas. Manusmriti: a text that served as a foundational legal and societal framework in ancient India. EWS: refers to the Economically Weaker Section, a government classification referring to those within the unreserved (general) category eligible for a 10% quota in government jobs and educational admissions. Karan Johar: an Indian filmmaker, producer and television personality. Dharavi: a residential area in Mumbai (Bombay) considered one of the world's largest slums. Adani: Gautam Adani is an Indian billionaire and chairperson of the multinational conglomerate, the Adani Group. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/sociology

This episode featured a conversation with Rahul Sonpimple, founder of the All-India Independent Scheduled Castes Association. Our conversation began with Rahul's conception of Indian history and the place of anti-caste struggle within it. We delved further into Rahul's own understanding of “anti-caste” as deeply rooted in Ambedkar's own argument about the necessity of force in emancipatory social transformation. Rahul was especially forthright about the political cost of elevating meekness as a moral condition, a choice that he associates with the rise of a Dalit middle class focused primarily on securing its own representational authority. This took us to a discussion of the need for an independent and consolidated Dalit politics rooted in the lives of the Dalit poor with sufficient leverage to negotiate terms with the state. The last part of the episode focused on Rahul's critique of both Ambedkarites and Indian Marxists for their disregard of caste as a material question. He spoke at particular length about the failure of Indian Marxists to advance a materalist critique of caste and how their analytical separation of caste and class has played into the hands of the Hindu Right. We ended the episode with Rahul laying out his own definition of Ambedkarism as a material and spiritual politics that recognizes the Dalit poor as a revolutionary class with the potential to rebuild society. Read the transcript here Guest Rahul Sonpimple is author and founder of the All-India Independent Scheduled Castes Association. References B.R. Ambedkar, The Buddha and his Dhamma, 1957. B.R. Ambedkar, Small Holdings in India and their Remedies, 1918. B.R. Ambedkar, Buddha or Karl Marx, 1956. B.R. Ambedkar, “Mr. Russell and the Reconstruction of Society,” 1916. Rahul Sonpimple, “Against Hindu Rashtra: Ambedkar's Buddhist Rashtra as Nation,” The Ambedkarian Chronicle, May 4, 2026. Rahul Sonpimple, “Remembering Babasaheb Ambedkar: The Unfinished Task of Burying Manu,” The Ambedkarian Chronicle, April 14, 2026. Rahul Sonpimple, “Kanshi Ram Sahab: Beyond Bureaucratic Dalit Passivity,” The Ambedkarian Chronicle, March 15, 2026. Rahul Sonpimple, “Spontaneity in Ambedkar: Beyond the Passivity of Popular Dalit Discourse,” The Ambedkarian Chronicle, April 16, 2025. Rahul Sonpimple, “The End of Independent Ambedkarite Dalit Politics?” Round Table India, July 12, 2024. Rahul Sonpimple, “Dalit conversions: An act of rebellion against caste supremacy,” Al Jazeera, 14 June 2018. Himsa and ahimsa are foundational ethical concepts in Buddhism. Himsa refers to injury, harm, or violence and ahimsa to non-harming, non-violence, or compassion. Ambedkar critiqued extreme, blanket doctrines of ahimsa as unworkable and often hypocritical. Chokhamela was a saint-poet from Maharashtra, India who belonged to the Mahar caste and was a devotee of Vitthala. Bhakt: devotee Vitthala: Hindu deity worshipped mainly in the states of Maharashtra and Karnataka as an avatar of Vishnu. Kabir and Ravidas: medieval poet-saints who were part of the Bhakti movement (7th-17th century), which emphasized devotion to a personal god, rather than rituals and scriptural knowledge, as the path to spiritual liberation. Samata Sainik Dal: a social organization founded by B. R. Ambedkar in 1927 with the objective of safeguarding the rights of all oppressed sections of Indian society. Bhima Koregaon: a village in Maharashtra that was the site of an 1818 battle between the army of Peshwa Baji Rao II and an East India Company force comprised mainly of Mahars, a Dalit caste. This battle has attained legendary status for Dalits who view it as a victory of Mahars over the Brahminical Peshwas. Baniya: refers to mercantile castes primarily from the states of Rajasthan and Gujarat. Kanshi Ram: Indian social reformer and politician who founded the All India Backwards and Minorities Communities Employees' Federation (BAMCEF) in 1971 and the Bahujan Samaj Party in 1984. Jogendra Nath Mandal: Bengali politician and Dalit leader who held the law portfolio in the 1946-47 Interim Government of India and served as the Minister of Law and Labor in Pakistan from 1947-50. Rajah: M.C. Rajah was a Tamil politician and Dalit leader who served on the Madras Legislative Council in the 1920s and founded the All India Depressed Classes Association in 1925. Kamble: B.C. Kamble was a Marathi politician and Dalit leader who led the Republican Party of India for decades. BAMCEF: All India Backwards and Minorities Communities Employees' Federation UGC Bill: officially the University Grants Commission (Promotion of Equity in Higher Education Institutions) Regulations, 2026, is a set of regulations aimed at ending discrimination against marginalized communities in higher education. Following widespread protests and a public interest litigation (PIL), the Supreme Court of India stayed the regulations in January 2026. Bhagwa kapda: saffron clothing Scheduled Caste Federation: a political organization founded in 1942 by Dr. B. R. Ambedkar dedicated to advocating for the rights and political self-representation of the Dalit community. Republican Party of India: a political party established by Dr. B. R. Ambedkar in 1956. PESA: Panchayats Extension to Scheduled Areas (PESA) Act, 1996 is a landmark legislation enacted by the Government of India to ensure self-governance for tribal communities living in Fifth Schedule Areas. Manusmriti: a text that served as a foundational legal and societal framework in ancient India. EWS: refers to the Economically Weaker Section, a government classification referring to those within the unreserved (general) category eligible for a 10% quota in government jobs and educational admissions. Karan Johar: an Indian filmmaker, producer and television personality. Dharavi: a residential area in Mumbai (Bombay) considered one of the world's largest slums. Adani: Gautam Adani is an Indian billionaire and chairperson of the multinational conglomerate, the Adani Group. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/south-asian-studies

Hey everyone... welcome back to The Malayali Podcast.Njan innu ningalodu oru simple question chodikan aanu vannirikkunnath."Exactly one year kazhinjal... ningalude life engane irikkum?"Seriously... close your eyes for a second.Oru varsham.365 days.Athrayum time-il enthellam sambhavikkam?New job.New city.New business.Marriage.Breakup.Promotion.Million subscribers.Or maybe... just finally becoming the person you've always wanted to be.You know...Oru year-il life full change aavan pattum.Pakshe...Most of us underestimate what one year can do.Nammal ellarum January first varumbo goals ezhuthum.Gym.Reading.Business.Learning AI.Saving money.January 10 aavumbo...Notebook drawer-il.Dreams postpone cheyyum.Because...Nammal oru mistake cheyyunnu.We overestimate what we can do in one week...But underestimate what we can do in one year.Imagine...Daily just 1 hour padichal...One year kazhinjal...365 hours.That's almost enough to become really good at a completely new skill.One small habit.One hour.Every day.That's how lives change.Not overnight.But over time.Enikku oru story parayam.Imagine two friends.Rahulum Arjunum.Both are 25.Both have the same salary.Same laptop.Same internet.Same opportunities.Rahul every day parayum..."Nale thudangam.""Ippo time illa.""I'll start after Onam.""After New Year."One year passes.Nothing changes.Arjun?Daily 30 minutes coding padichu.Weekend-il freelancing start cheythu.LinkedIn-il content post cheythu.AI tools padichu.One year later...Same person.Different life.Difference?Not talent.Not luck.Just...He started.Last one week news nokkiyal...Almost every day AI-il puthiya updates varunnu.Companies are hiring people who know how to work with AI—not because AI replaces everyone, but because people who use AI effectively often work faster and smarter.Every week...Someone launches a startup.Someone gets funding.Someone builds an app over a weekend.Someone uploads their first YouTube video.Someone quits their job.Someone gets their dream job.Someone starts learning at age 40.Someone changes their life at age 60.News nammale oru karyam padhippikkunnu.The world doesn't wait.Technology doesn't wait.Time doesn't wait.Question is...Will you?Njan oru karyam notice cheythittund.People think confidence comes first.Actually...Confidence comes after action.Nobody starts confident.The first podcast...Awkward.First video...Cringe.First business...Probably fails.First speech...Hands shake.First gym day...Embarrassing.Pakshe...Second time becomes easier.Tenth time becomes normal.Hundredth time...That's your identity.Self-belief isn't born.It's built.Imagine...Exactly one year from today.You wake up.You open your phone.Bank account is healthier.Mind is calmer.Body feels stronger.Family is proud.You're living in a different city.Maybe even a different country.Or maybe...You're still in the same place.But you're a completely different person.Because...You decided to start.One decision.One year.A completely different life.So today...I don't want you to promise yourself ten things.Just one.Start.Not tomorrow.Not Monday.Not next month.Today.Because...Oru year passes really fast.And one year from now...You'll either say..."I'm so glad I started."Or..."I wish I had started."The choice is yours.Live your life.Ellam nannayi aavum.Trust the process.This is Krishnalal, and you're listening to The Malayali Podcast.See you in the next episode.Take care. ❤️INTRO (0:00 – 1:00)PART 1 – The One-Year Illusion (1:00 – 3:00)PART 2 – A Story About Two Friends (3:00 – 5:00)PART 3 – What Happened This Week? (5:00 – 7:00)PART 4 – My Own Observation (7:00 – 8:30)PART 5 – Imagine Future You (8:30 – 9:30)OUTRO (9:30 – 10:00)

In this episode of Run the Numbers, CJ sits down with Rogo president Rahul Rekhi to unpack what AI actually changes in investment banking and finance. They dig into token economics, why adoption without ROI is a trap, how vertical AI wins, and why domain expertise still matter.—SPONSORS:Pulley is an equity management platform that lets you issue options, model dilution, and complete 409As without your cap table turning into a spreadsheet disaster. Founders raising, hiring, and scaling use Pulley to keep equity clean and stay focused on building. Learn more or request a demo at https://pulley.com/mostlymetricsRillet is an AI-native ERP built for modern finance teams that want to replace NetSuite and close faster. With revenue recognition, close management, multi-entity support, and native Stripe and Salesforce integrations, Rillet helps scaling companies run their finance stack in one place. Hundreds of teams, including Windsurf and Mercor, use Rillet to make the zero-day close real. Book a demo at https://www.rillet.com/cjMaximor is an autonomous finance platform that runs order-to-cash, procure-to-pay, the close, cash management, and reporting on self-learning agents instead of a dozen disconnected tools. One PE-backed customer cut their close in half, took audit findings from seven to zero, and cut back-office costs by 70% in six months. You pay for outcomes, not seats. See it at https://www.maximor.ai/Brex is an intelligent finance platform with AI-powered agents that capture expenses automatically, enforce policy before the spend happens, and close your books in minutes instead of weeks. 35,000+ companies like OpenAI, Coinbase, Anthropic, and DoorDash already run on Brex. It's time to get Brex AF. Learn more at https://www.brex.com/metricsAnrok is the sales tax platform that watches your exposure everywhere, automates compliance, and flags risk before it turns into a surprise back-tax letter from a state you've never set foot in. Companies like Anthropic, Notion, and Vanta already trust Anrok to stay ahead of rules that move faster than any spreadsheet can. Talk to a sales tax expert for a personalized exposure estimate at https://www.anrok.com/rtnRightRev is an automated revenue recognition platform that lets your product team ship new pricing without asking finance for permission, and your sales team close deals without creating downstream chaos. Check out their free tool at calculator.rightrev.com It scores your rev rec process, shows what's exposing you to risk, and tells you exactly where to focus before it bites you in the rear end. Check it out at https://calculator.rightrev.com—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNGuest: https://www.linkedin.com/in/rahulrekhi/Company: https://www.rogo.ai/CJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:A CFO Explains the Stock Exchangeshttps://youtu.be/pooOE6ZNGR4A CFO Explains Marketplaceshttps://youtu.be/LpbH9GpBrSY—TIMESTAMPS:0:00 Preview and Intro2:44 Why finance was first to verticalize AI6:28 What the president title means at Rogo9:55 Sponsors — Pulley | Rillet | Maximor13:02 The problem Rogo is solving16:16 Token maxing is not transformation17:43 Why ROI is so hard to measure19:39 Sponsors — Brex | Anrok | RightRev22:37 ROI is business-unit specific24:03 Budgeting tokens like a benefits load25:00 AI incentives aren't aligned to efficiency26:26 The model broker function32:03 Not all token spend is equal37:14 Who owns AI efficiency?40:59 The forward deployed banker43:00 Domain expertise: the Interstellar analogy49:21 Lightning round49:28 Screwed up: DCF error in a live deal51:13 Will new grads have the spidey sense?53:03 Meeting Pope Francis55:04 Fact-checking jobs numbers at the White House57:39 Advice to younger self59:21 Credits

Martin and Rahul are BACK to talk all things 3x3 once again!The guys recap what has been a ROLLERCOASTER of a 3x3 season so far - from the World Cup to the Women's Series. They also look ahead towards a wild second half of action, led by the iconic FIBA 3x3 Europe Cup. All that and more in this episode!

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

Praticien holistique d'origine indienne, Rahul Bharti ranime la mémoire des sagesses ancestrales du monde, celles qui nous enseignent l'écoute du corps, de l'âme et de la vie tout autour.Il y a 30 ans, il a créé au Népal le Healing Hands Center, un centre international pour transmettre ses enseignements, reçus en vivant dès le plus jeune âge avec différentes tribus et enseignants du monde entier, notamment des chamans du Sri Lanka et un grand sage aveugle thaïlandais. Fort de cette transmission unique, remontant à la source de savoirs et pratiques millénaires (massages thaï anciens, pratiques énergétiques profondes, bols tibétains), Rahul Bharti porte un regard inédit sur les déséquilibres de notre temps et sur les chemins possibles de leur transformation.Il nous présente son livre : "L'école de l'âme, là où la vie enseigne et l'âme mûrit" aux éditions Trédaniel.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Welcome to our brand-new storytelling adventure, "Panchatantra Life Lessons with Ananya and Rahul"!In this special series, Rahul faces everyday problems just like many children do. His wise elder sister, Ananya, helps him learn important life lessons through the timeless wisdom of Panchatantra stories.In this series, you will enjoy:

#PanchatantraStories#KidsStories#MoralStories#EnglishStoriesForKids#StorytellingForKids#BedtimeStoriesWelcome to our brand-new storytelling adventure, "Panchatantra Life Lessons with Ananya and Rahul"!In this special series, Rahul faces everyday problems just like many children do. His wise elder sister, Ananya, helps him learn important life lessons through the timeless wisdom of Panchatantra stories.In this series, you will enjoy:

Most conventional accounts of the origins of liberalism in India typically begin and end with the British. Indian thinkers are often depicted as encountering liberal ideas through colonial institutions, adapting them to local conditions, and eventually turning them against the British Raj.  But a new book by Rahul Sagar, The Birth of Indian Liberalism: Mama Parmanand's Letters to an Indian Raja, uncovers an older tradition of Indian liberal thought through a remarkable work first published in 1891 and then largely forgotten for more than a century. In a series of incisive letters addressed to the native ruler of Baroda, Parmanand argued that India's native princes should embrace constitutional government, cultivate liberal values, and liberate their subjects from oppressive customs, social hierarchies, and arbitrary state power.  To talk more about Parmanand's life, the rediscovery of his letters, and what they tell us about the origins of Indian liberalism, Rahul Sagar joins Milan on the show this week for the season finale of Grand Tamasha. Rahul is Global Network Associate Professor of Political Science at New York University Abu Dhabi and a leading scholar of modern Indian political thought. He previously taught at Princeton University and Yale-NUS College. He is the author or editor of several books, including To Raise a Fallen People and The Progressive Maharaja. Episode notes: 1.        “India's Hidden Treatise on Statecraft (with Rahul Sagar),” Grand Tamasha, November 1, 2022.  2.        “What Kind of World Power Does India Want to Be (with Rahul Sagar),” Grand Tamasha, June 1, 2022. 3.        Rahul Sagar, Ideas of India, database.

Preventive medicine flips the script on how we usually handle our healthcare: Instead of waiting until something breaks, you catch issues earlier, when they're easier to address. In this episode, Rahul Iyengar, MD, explains why our current "sick care" system tends to wait for symptoms before stepping in — and what a more proactive model looks like.    He also shares why relationship-based care that gives providers more time with patients tends to lead to better outcomes, and how lasting health comes from sustainable habits rather than quick fixes. He offers a clear, practical look at taking charge of your health on your own terms.   Find the episode highlights, get related resources and view the transcript for this episode at https://experiencelife.lifetime.life/podcast/prevent-vs-react-why-taking-a-proactive-approach-to-your-health-matters-with-rahul-iyengar-md   Have thoughts you'd like to share or topic ideas for future episodes? Email us at lttalks@lt.life — we'd love to hear from you!   Follow us on Instagram: @lifetime.life   The information in this podcast is intended to provide broad understanding and knowledge of healthcare topics. This information is for educational purposes only and should not be considered complete and should not be used in place of advice from your physician or healthcare provider. We recommend you consult your physician or healthcare professional before beginning or altering your personal exercise, diet or supplementation program. 

Eight decades after independence, India still isn't free. Rahul Ahluwalia joins Amit Varma in episode 447 of The Seen and the Unseen to explain why economic growth has such a positive humanitarian impact -- and freedom lies at its heart. (FOR FULL LINKED SHOW NOTES, GO TO SEENUNSEEN.IN.) Also check out: 1. Rahul Ahluwalia on Twitter, LinkedIn and FED. 2. Foundation for Economic Development. 3. Growth is Good -- Rahul Ahluwalia's podcast at FED. 4. Deepak VS and the Man Behind His Face — Episode 373 of The Seen and the Unseen. 5. Swaminathan Aiyar's columns at ToI and his own website. 6. Gurcharan Das's columns at ToI and his own website. 7. India Unbound — Gurcharan Das. 8. The Life and Times of Gurcharan Das — Episode 425 of The Seen and the Unseen. 9. The Importance of the 1991 Reforms — Episode 237 of The Seen and the Unseen (w Shruti Rajagopalan and Ajay Shah). 10. The Life and Times of Montek Singh Ahluwalia — Episode 285 of The Seen and the Unseen. 11. The Forgotten Greatness of PV Narasimha Rao — Episode 283 of The Seen and the Unseen (w Vinay Sitapati). 12. Naushad Forbes Wants to Fix India — Episode 282 of The Seen and the Unseen. 13. The Life and Times of KP Krishnan — Episode 355 of The Seen and the Unseen. 14. Lant Pritchett Is on Team Prosperity — Episode 379 of The Seen and the Unseen. 15. The Life and Times of the Indian Economy -- Episode 387 of The Seen and the Unseen (w Rajeswari Sengupta). 16. Why Freedom Matters — Episode 10 of Everything is Everything. 17. The Reformers — Episode 28 of Everything is Everything. 18. India's Massive Pensions Crisis — Episode 347 of The Seen and the Unseen (w Ajay Shah & Renuka Sane). 19. The Tragedy of Our Farm Bills — Episode 211 of The Seen and the Unseen (w Ajay Shah). 20. The 1991 Project. 21. Stay Away From Luxury Beliefs -- Episode 46 of Everything is Everything. 22. Gig Work is AWESOME! -- Episode 124 of Everything is Everything. 23. Reading Lolita in Tehran -- Azar Nafisi. 24. India's Problem is Poverty, Not Inequality -- Amit Varma. 25. A Venture Capitalist Looks at the World — Episode 213 of The Seen and the Unseen (w Sajith Pai). 26. Public Choice Theory Explains SO MUCH -- Episode 33 of Everything is Everything. 27. Population Is Not a Problem, but Our Greatest Strength -- Amit Varma. 28. The short history of global living conditions and why it matters that we know it -- Max Roser. 29. The Florentines -- Paul Strathern. 30. National output without government? State capacity and welfare measurement -- Vincent Geloso and Chandler Reilly. 31. Atlas Shrugged -- Ayn Rand. 32. The Wealth of Nations -- Adam Smith. 33. Understanding the State -- Episode 25 of Everything is Everything. 34. Every Act of Government Is an Act of Violence -- Amit Varma. 35. Economic growth is enough and only economic growth is enough — Lant Pritchett with Addison Lewis. 36. Where Has All the Education Gone? — Lant Pritchett. 37. Looking like a state: The seduction of isomorphic mimicry -- Matt Andrews, Lant Pritchett and Michael Woolcock. 38. Sixteen Stormy Days — Tripurdaman Singh. 39. The First Assault on Our Constitution — Episode 194 of The Seen and the Unseen (w Tripurdaman Singh). 40. Nehru: The Debates that Defined India — Tripurdaman Singh and Adeel Hussain. 41. Nehru's Debates — Episode 262 of The Seen and the Unseen (w Tripurdaman Singh and Adeel Hussain). 42. The Right to Property — Episode 26 of The Seen and the Unseen (w Shruti Rajagopalan). 43. Caged Tiger: How Too Much Government Is Holding Indians Back — Subhashish Bhadra. 44. Subhashish Bhadra on Our Dysfunctional State — Episode 333 of The Seen and the Unseen. 45. Colours of the Cage: A Prison Memoir — Arun Ferreira. 46. Shikha Dalmia Is the Unpopulist -- Episode 403 of The Seen and the Unseen. 47. DeMon, Morality and the Predatory Indian State — Episode 85 of The Seen and the Unseen (w Shruti Rajagopalan). 48. Narendra Modi Takes a Great Leap Backwards — Amit Varma. 49. Horseshoe Theory and the Median Voter Theorem. 50. Government's End: Why Washington Stopped Working — Jonathan Rauch. 51. Denial: My 25 Years Without a Soul -- Jonathan Rauch. 52. The Logic of Collective Action -- Mancur Olson. 53. Anarchy, State and Utopia — Robert Nozick. 54. A Theory of Justice — John Rawls. 55. India After Gandhi — Ramachandra Guha. 56. Arguments for Liberty -- Edited by Aaron Ross Powell and Grant Babcock. 57. Johan Norberg on Amazon and YouTube. 58. State Building -- Francis Fukuyama. 59. India Needs Decentralization -- Episode 47 of Everything is Everything. 60. Fixing Indian Education — Episode 185 of The Seen and the Unseen (w Karthik Muralidharan). 61. Education in India — Episode 77 of The Seen and the Unseen (w Amit Chandra). 62. The Profit Motive in Education — Episode 9 of The Seen and the Unseen (w Parth Shah). 63. Our Unlucky Children (2008) -- Amit Varma. 64. Fund Schooling, Not Schools (2007) -- Amit Varma. 65. Profit = Philanthropy -- Amit Varma. 66. Praise for intelligence can undermine children's motivation and performance — Claudia Mueller and Carol Dweck. 67. Controlling Your Dopamine For Motivation, Focus & Satisfaction -- Huberman Lab. 68. Master Your Sleep & Be More Alert When Awake -- Huberman Lab. 69. Why We Sleep — Matthew Walker. 70. Matthew Walker on the Huberman Lab podcast. 71. The Frido 3D eye mask Amit uses. 72. John Collison's tweet on the world being a museum of passion projects. 73. The Beatles, Elvis Presley, Dean Martin, Metallica, Black Sabbath and Iron Maiden on Spotify. 74. Love Me Tender and Can't Help Falling in Love -- Elvis Presley. 75. Aaj -- Bloodywood. 76. Bekhauf -- Bloodywood (featuring BABYMETAL) 77. Coke Studio Bharat Season 2 and Season 3. 78. Dr Dre, Snoop Dogg and Eminem on Spotify. 79. The Next Episode -- Dr Dre featuring Snoop Dogg, Kurupt, Nate Dogg. 80. Ravi Shankar at Monterey Pop. 81. Ain't No Man Alive Can Handle Me -- Dumpster Grooves. 82. Alistair MacLean and PG Wodehouse on Amazon. 83. The Ultimate Hitchhiker's Guide to the Galaxy -- Douglas Adams. 84. Animal Farm -- George Orwell. 85. Building State Capability: Evidence, Analysis, Action -- Matt Andrews, Lant Pritchett and Michael Woolcock. 86. The Rebirth of Education: Schooling Ain't Learning -- Lant Pritchett. 87. Lant Pritchett On Growth, Development & Income Inequality -- FED Dialogues. 88. In Service of the Republic — Vijay Kelkar & Ajay Shah. 89. Random Critical Analysis. 90. Chupke Chupke -- Hrishikesh Mukherjee. Amit Varma runs a course called Life Lessons, which aims to be a launchpad towards learning essential life skills all of you need. For more details, and to sign up, click here. And have you read Amit's newsletter? It's madly active right now! Subscribe right away to The India Uncut Newsletter! It's free! Also check out Amit's online course, The Art of Clear Writing. Episode art: 'Marketplace of Ideas' by Simahina.

I have told Rahul's story and now two years after he survived the worst depression, he tells his story from the beginning of how depression almost took his life away to finding his light and himself again! I really hope that this episode gives you hope if you are struggling mentally and know that you matter ❤️

How does someone who never ran growing up become a Boston Marathon qualifier and sub-3-hour marathoner? In this episode of The Lebanese Physicians Podcast, Rahul Nandi shares his remarkable journey from running his first marathon in India to completing more than 50 marathons and chasing a sub-2:50 finish. We discuss consistency, training, mindset, nutrition, injury prevention, and the lessons running teaches about life. Whether you're training for your first 5K or your next marathon, this conversation is packed with practical advice and inspiration. #Running #Marathon #BostonMarathon #EnduranceSports On YouTube @thelebanesephysicianspodcast

In this episode, Lera—our special Academy member—joins Debora and Rahul to unravel a fascinating case of a young man with neurological symptoms that takes an unexpected and incredible turn. Presented by Mark, this diagnostic journey will keep you guessing until the very end. Don't miss this compelling path to the final diagnosis! To join us… Read More »Episode 462 – The Clinical Unknown Series with Lera Novotnaia

In this clip from Transfer Insight, Dan spoke to Rahul from the Tika Tapas Podcast to get the lowdown from La Liga on Liverpool's new signing. Hosted on Acast. See acast.com/privacy for more information.

In this episode of the WP Tavern Jukebox podcast, the conversation focused on agency growth, lessons from rtCamp's journey, and the changing agency landscape due to AI. We discussed the importance of hiring complementary skill sets when starting an agency, and the necessity to niche down for success in 2026, rather than being a generalist WordPress agency. The discussion explored rtCamp's bold commitment to integrating AI throughout their business operations to improve efficiency and reduce costs, and how this positions them for future growth while transforming traditional agency roles and services.

In this episode of the WP Tavern Jukebox podcast, the conversation focused on agency growth, lessons from rtCamp's journey, and the changing agency landscape due to AI. We discussed the importance of hiring complementary skill sets when starting an agency, and the necessity to niche down for success in 2026, rather than being a generalist WordPress agency. The discussion explored rtCamp's bold commitment to integrating AI throughout their business operations to improve efficiency and reduce costs, and how this positions them for future growth while transforming traditional agency roles and services.

What does it actually take to build AI for 70 crore users?Vikram sits down with Rahul Chowdhury -  co-founder and CTO of PhonePeto talk about how India's most scaled fintech is approaching AI. Not with hype or a top-down mandate, but with a quiet, deliberate, engineering-first philosophy that started four years ago with a small team focused on making developers happier.Rahul shares the inside story of PhonePe's AI journey from building their own LLM gateway and Agent Hub, to launching AI search with Microsoft, to betting on on-device models for privacy and cost. And it ends with the biggest idea of all: India's DPI stack has spent a decade making data AI-ready. The opportunity now is to use it to build the bank branch of one — truly personalized financial products for every Indian.If you're a founder, engineer, or product leader trying to understand where India's AI story is really headed, don't miss this.What you'll learn

Ben Pruitt is back with a Brand New Season of Bending Not Breaking Featuring Co-Hosts from Across the BNB Patreon Community! This Week : Ben is joined by returning Patrons Kelly, Maggie, & Rahul to discuss The Legend of Korra S1E9 : Out of the Past, through the Lens of LEGACY. Follow : @bnb_pod & @thearkofenetwork on Instagram Music : "Searching Endlessly" by nARK Produced By Noah Blanchard Released By The ARK of E Network Send Feedback : thearkofe@gmail.com

Grief, Gratitude, and Remembering True Nature After My Father's PassingHost Rahul N Singh returns to The Bearded Mystic Podcast after a break and shares that his father died last month, reflecting on grief, regrets, and learning to face loss directly without denying emotions or spiraling in them. He describes finding steadiness through prayer, simran, and witnessing feelings, emphasizing that memories remain and that his father was a major influence on his spirituality. Rahul expresses gratitude for being present in his father's final moments and for support from community, family, friends, and his wife, noting the importance of staying connected rather than withdrawing from spirituality. He highlights non-dual teachings about abiding as pure consciousness, remembering one's true nature, and viewing death through the lens of oneness, including references to Nij Gar and the Bhagavad Gita.Send us Fan MailSupport the showSupport me via Paypal: https://www.paypal.biz/beardedmysticJoin our Discord Server: https://discord.gg/hnRf7wESwXVisit my website: https://www.thebeardedmysticpodcast.com/Want a one-on-one spiritual discussion with The Bearded Mystic - book here: https://www.thebeardedmysticpodcast.com/p/spiritual-discussion/You can follow me and contact me on social media:TikTok: https://vm.tiktok.com/ZMdk3HPJh/Instagram: https://www.instagram.com/thebeardedmysticpodcast/YouTube: https://www.youtube.com/c/TheBeardedMysticPodcast/Facebook: https://www.facebook.com/The-Bearded-Mystic-PodcastBluesky:  https://bsky.app/profile/beardedmystic.bsky.socialBecome a Patron: https://www.patreon.com/thebeardedmysticpodcast

Fluent Fiction - Hindi: From Shadows to Spotlight: Rahul's Artistic Revelation Find the full episode transcript, vocabulary words, and more:fluentfiction.com/hi/episode/2026-06-11-07-38-19-hi Story Transcript:Hi: मुंबई के एक ऊँचे स्कूल में गर्मियों की तपती धूप के बीच सांस्कृतिक महोत्सव की धूम थी।En: In a prestigious school in Mumbai, amidst the scorching summer heat, there was a hustle and bustle of a cultural festival.Hi: स्कूल के गलियारों में बच्चों की खिलखिलाती हंसी और रंग-बिरंगे सजावट की चमक थी।En: The school's corridors echoed with children's laughter, and colorful decorations shone brightly.Hi: चारों ओर उत्साह का माहौल था।En: There was an atmosphere of enthusiasm all around.Hi: इसी भीड़-भाड़ में राहुल भी था, अपनी चित्रकारी क्लास से निकलकर स्कूल के आर्ट गैलरी के पास खड़ा था, मन में संकोच के साथ।En: Amidst this crowd was Rahul, standing near the school's art gallery after leaving his art class, with hesitation in his heart.Hi: राहुल अब तक सिर्फ अपने स्केचबुक में ही अपनी कला को छिपा कर रखता था।En: Rahul had so far only kept his art hidden in his sketchbook.Hi: उसे अपनी पेंसिल और रंगों की दुनिया से प्यार था, लेकिन वह डरता था कि लोग उसे कैसे जज करेंगे।En: He loved the world of pencils and colors, but he feared how people would judge him.Hi: उसके मन में एक ही उलझन थी — अगर आर्ट शो में उसका नाम नहीं होगा, तो उसकी कला कैसे देखी जाएगी?En: He had only one dilemma — if his name wasn't in the art show, how would people see his art?Hi: दूसरी ओर, अनिका थी, जो बेहद मिलनसार और उत्साही थी।En: On the other hand, there was Anika, who was very social and enthusiastic.Hi: वह इस महोत्सव की पूरी जिम्मेदारी संभाल रही थी।En: She had taken full responsibility for this festival.Hi: आर्ट शो की तैयारी में वह इस उत्सुकता से लगी थी कि स्कूल के सारे कलाकारों की कला दुनिया के सामने आए।En: She was eagerly preparing for the art show, wanting all the artists of the school to showcase their art to the world.Hi: हालांकि, वह राहुल के अंदर छिपी कला से अनजान थी।En: However, she was unaware of the art hidden inside Rahul.Hi: एक पूरा दिन बीत गया, छात्रों का आर्ट शो में नामांकन जारी था।En: A whole day passed, and the enrollment for the students in the art show continued.Hi: मगर राहुल के मन की सहम उठे कदमों पर भारी पड़ रही थी।En: Yet, the hesitation in Rahul's mind was weighing down his hesitant steps.Hi: उसने भले ही कागज पर दर्जनों चित्र बनाए थे, पर वह नामांकन पत्र पर एक भी हस्ताक्षर नहीं कर पाया था।En: Although he had created dozens of drawings on paper, he couldn't bring himself to sign a single enrollment form.Hi: महोत्सव का दिन आ ही गया।En: The day of the festival finally arrived.Hi: अनिका ने अंतिम घोषणा करते हुए कहा, "आखिरी वक्त है, जो भी छात्र अपनी कला प्रदर्शित करना चाहता है, जल्दी से नामांकन कराए।En: Anika made a final announcement, saying, "This is the last moment; any student who wants to showcase their art, please register quickly."Hi: "राहुल ने नजरें उठाईं, सामने अनिका खड़ी थी, उसके चेहरे पर एक मुस्कान थी, जैसे वह कह रही हो — "चलो, सामने आओ।En: Rahul looked up, and there stood Anika, with a smile on her face, as if saying, "Come on, step forward."Hi: " राहुल का दिल उसके कदमों से तेज धड़क रहा था।En: Rahul's heart was beating faster than his steps.Hi: उसने गहरी सांस भरी और अपनी झिझक पर विजय पाने की कोशिश में आगे बढ़ा।En: He took a deep breath and, in an attempt to conquer his hesitation, moved forward.Hi: आखिरकार, उसने अपना नाम दर्ज कराया।En: Eventually, he registered his name.Hi: उसकी पेंटिंग आर्ट शो में सबसे आगे लगाई गई।En: His painting was placed at the forefront of the art show.Hi: जब लोग उसकी पेंटिंग देखते, तो तारीफों की झड़ी लग जाती।En: When people looked at his painting, praises poured in continuously.Hi: "वाह!En: "Wow!"Hi: " "कितना सुंदर चित्र!En: "What a beautiful picture!"Hi: " हर आवाज उसकी आत्मा को ऊँचाई पर ले जा रही थी।En: Every voice was lifting his spirit higher.Hi: उस दिन के बाद से, राहुल ने अपने अंदर की कला को दुनिया के सामने लाने में हिचकिचाहट महसूस नहीं की।En: Since that day, Rahul no longer felt hesitation in bringing his art to the world.Hi: उसका आत्मविश्वास लगभग उस समय की तरह चमक उठा, जैसे मुंबई की तेज धूप।En: His confidence shone almost like the bright sunlight of Mumbai.Hi: उसने समझ लिया, जब तक वह नहीं दिखाएगा, लोग नहीं देख पाएंगे।En: He understood that unless he showed his art, people wouldn't be able to see it.Hi: उस गर्मियों के महोत्सव ने बेशक राहुल को बदल दिया था।En: That summer festival certainly changed Rahul.Hi: अब वह कला को अपनी आवाज समझने लगा था, और लोग खुशी-खुशी उसकी सुनने के लिए तैयार थे।En: Now he understood art as his voice, and people were happily ready to listen to it. Vocabulary Words:prestigious: ऊँचेscorching: तपतीhustle and bustle: धूमdecorations: सजावटenthusiasm: उत्साहhesitation: संकोचsketchbook: स्केचबुकdilemma: उलझनenrollment: नामांकनhesitant: हिचकिचाहटpraises: तारीफोंconquer: विजयforefront: सबसे आगेspirits: आत्माconfidence: आत्मविश्वासechoed: गूँजतीanonymous: अनजानsocial: मिलनसारresponsibility: जिम्मेदारीannouncement: घोषणाregister: दर्जcultural: सांस्कृतिकgallery: गैलरीjudged: जजunaware: अनजानfear: डरart show: आर्ट शोsketch: चित्रकारीpainting: पेंटिंगartists: कलाकारों

It's not just about rockets. This week, Michelle, Rahul and Will explore one of the most anticipated stock market debuts in history: the SpaceX IPO. With a potential $1.75 trillion valuation and intense global investor interest, it's widely tipped as one of the biggest market launches ever. But can the company live up to the hype — or is this Elon Musk's biggest gamble yet? Plus: what does SpaceX actually do, and why does it matter to investors?This is the latest episode of our weekly Power Players show, hosted by Rahul Tandon and Will Bain in the UK, and North America Business Correspondent Michelle Fleury in New York.Producer: Rebecca SmyllieYou can email the team: businessdaily@bbc.co.uk(Picture: Tesla and SpaceX's CEO Elon Musk reacts during an event in London, UK in 2023. Credit: Kirsty Wigglesworth/Pool via REUTERS/File Photo)

Join Priya and Rahul on a journey as they discover how junk food can affect their body and mind, and how Guruma's special 49-Day Detox Program can help them feel healthier, happier, and full of energy.Learn about nature's superfoods and ways to grow stronger, brighter, and healthier from the inside out.Join For e-mail registration: https://dbsky.me/detox2026-kHMQk94V

In this episode, Rahul Vanjani, Co-Founder of ITO Health, Assistant Professor of Medicine at Brown University, and Medical Director at Amos House, discusses the intersection of addiction medicine, social determinants of health, and Medicaid policy. He shares insights on the coming Medicaid changes, their impact on vulnerable populations, and how healthcare organizations can help patients maintain access to critical coverage and care.

This week, Michelle, Rahul and Will explore the world of dynamic pricing, where prices go up when demand is high and come down when demand drops. It's already standard in travel and hospitality. Now, it's expanding into live events, and this year, it reached the World Cup. Supporters say it's simple economics, charging what people are willing to pay. Critics argue it risks pricing ordinary fans out of the experiences they love. So how does dynamic pricing really work? Why has it become one of the most controversial trends in live entertainment? And as organisers push to maximise revenue, are we seeing the future of events, or the point where fans push back?Hosts: Will Bain, Michelle Fleury and Rahul Tandon Producer: Rebecca Smyllie(Picture: The 2026 FIFA World Cup logo is placed over the original logo of the Hard Rock stadium in Miami, Florida, USA. Credit: CRISTOBAL HERRERA-ULASHKEVICH/EPA/Shutterstock)

•⁠ ⁠மீண்டும் வெற்றிச் சரிதத்தை எழுதுவோம் - மு.க.ஸ்டாலின்•⁠ ⁠கலைஞருக்கு புகழாரம் சூட்டிய விஜய், ராகுல்!•⁠ ⁠கருணாநிதி சிலைக்கு அமைச்சர் ராஜ்மோகன் மரியாதை•⁠ ⁠ஆட்சியைதான் 6 மாதங்கள் கழித்து விமர்சிப்போம் எனச் சொன்னோம்..” -ஆ.ராசா•⁠ ⁠"மராட்டிய அரசால் சாத்தியமாகும் பயிர்க் கடன் தள்ளுபடி, தமிழ்நாட்டில் சாத்தியமாகாதது ஏன்?" -அன்புமணி ராமதாஸ் கேள்வி•⁠ ⁠"முதலமைச்சர் விஜய் தனது தனிப்பட்ட பாதுகாவலருடன் வலம் வருவது ஏன்?" - இன்பதுரை எம்.பி. 5 கேள்விகள்.•⁠ ⁠மாவட்டங்களுக்கு பொறுப்பு அமைச்சர்கள் நியமனம்!•⁠ ⁠காங்கிரஸுக்கு ராஜ்ய சபா சீட் ஒதுக்கிய தவெக!•⁠ ⁠அண்ணாமலையை சமாதானப்படுத்தும் முயற்சி தோல்வி?•⁠ ⁠எங்க கட்சி பேரு கூட சொல்ல மாட்டேங்கிறீங்க. நாங்க என்ன தீண்ட தகாத கட்சியா?- ஆர்.பி.உதயகுமார் வேதனை•⁠ ⁠எஸ்.பி.வேலுமணியி ‘துரோகி' என முழக்கமிட்ட அதிமுக தொண்டர்?•⁠ ⁠கர்நாடக முதலமைச்சராக டி.கே.சிவக்குமார் இன்று மாலை பதவியேற்பு?•⁠ ⁠CBSE தலைவர் & செயலாளர் மாற்றம்?•⁠ ⁠ஐநா பொதுச்சபையின் தலைவர் பதவிக்கான தேர்தலில் வங்கதேசம் வெற்றி?•⁠ ⁠வரலாறு காணாத வெப்பம் பதிவாகும்.. 'எல் நினோ' குறித்து உலக வானிலை அமைப்பு எச்சரிக்கை!•⁠ ⁠உக்ரைன் மீது தாக்குதல் நடத்திய ரஷ்யா?•⁠ ⁠மீண்டும் தாக்குதலை தொடங்கிய அமெரிக்கா - ஈரான்?

Around 2016, buoyed by so-called data kranti  ("data revolution"), an aspirational neo-middle class of users in India accessed internet for the first time on their mobile phones. Unlimited: Aspirational Politics and Mobile Media Distribution (MIT Press, 2026) tells the story of digital infrastructures that are being created by state-corporations for content and money to move and reach such users. It interrogates how their design impact the forms of inclusions and exclusions enacted as well as the horizon of social behaviors and expectations in "Digital India." The book contends that to understand the possibilities and limits of India's aspirational politics, media studies scholars should attend to infrastructures of aspiration: the distributional logistics of streaming content and mobile money are the infrastructural backbone that recalibrate thresholds of aspirational goals.  Digital content media distribution is also shaped by how user practices get entangled with particular affordances of platforms, and hence the need to study both participatory cultures of circulation and logistics of distribution together. Drawing on in-depth interviews, ethnographic fieldwork, critical discourse analysis and participant observation, the book traces the supply chains of content delivery networks enabling streaming video-on-demand services and informal ways of circulating "vernacular" music videos through memory cards. Unlimited does not restrict itself to formal media infrastructures, but also researches online phishing and lending scam assemblages to understand how such scams perform critical boundary work to reveal the cracks in and workings of financial distribution networks. This book offers a systematic examination of distribution considerations—including localization strategies—required for imagining mobile phone users across the varied regional geographies of "Digital India." Rahul Mukherjee is Associate Professor of TV & New Media and graduate chair in the Department of Cinema & Media Studies at University of Pennsylvania. His teaching and research focus on the logistical and environmental dimensions of digital infrastructures and platforms. Rahul is the author of the monograph Radiant Infrastructures, and his work has been published in Critical Inquiry, SM+S, New Media & Society, and Science, Technology & Human Values. He has co-edited a special issue on "Media Power in Digital Asia" for Media, Culture & Society journal.   Priyam Sinha is an Alexander Von Humboldt Postdoctoral Research Fellow at the Institute for Asian and African Studies, Humboldt University in Berlin. Her research interests lie at the intersection of critical media industry studies, disability studies, gender studies, affect studies, production culture studies, and anthropology of the body, and her work has been published in the European Journal of Cultural Studies, Media, Culture and Society; Communication, Culture and Critique; South Asian Diaspora, among others. She is also a regular podcast host at the New Books Network and has been published in public writing forums like the Economic and Political Weekly, FemAsia, Asian Film Archive, among others. More information on her ongoing projects can be found on her website and you can follow her on X. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Around 2016, buoyed by so-called data kranti  ("data revolution"), an aspirational neo-middle class of users in India accessed internet for the first time on their mobile phones. Unlimited: Aspirational Politics and Mobile Media Distribution (MIT Press, 2026) tells the story of digital infrastructures that are being created by state-corporations for content and money to move and reach such users. It interrogates how their design impact the forms of inclusions and exclusions enacted as well as the horizon of social behaviors and expectations in "Digital India." The book contends that to understand the possibilities and limits of India's aspirational politics, media studies scholars should attend to infrastructures of aspiration: the distributional logistics of streaming content and mobile money are the infrastructural backbone that recalibrate thresholds of aspirational goals.  Digital content media distribution is also shaped by how user practices get entangled with particular affordances of platforms, and hence the need to study both participatory cultures of circulation and logistics of distribution together. Drawing on in-depth interviews, ethnographic fieldwork, critical discourse analysis and participant observation, the book traces the supply chains of content delivery networks enabling streaming video-on-demand services and informal ways of circulating "vernacular" music videos through memory cards. Unlimited does not restrict itself to formal media infrastructures, but also researches online phishing and lending scam assemblages to understand how such scams perform critical boundary work to reveal the cracks in and workings of financial distribution networks. This book offers a systematic examination of distribution considerations—including localization strategies—required for imagining mobile phone users across the varied regional geographies of "Digital India." Rahul Mukherjee is Associate Professor of TV & New Media and graduate chair in the Department of Cinema & Media Studies at University of Pennsylvania. His teaching and research focus on the logistical and environmental dimensions of digital infrastructures and platforms. Rahul is the author of the monograph Radiant Infrastructures, and his work has been published in Critical Inquiry, SM+S, New Media & Society, and Science, Technology & Human Values. He has co-edited a special issue on "Media Power in Digital Asia" for Media, Culture & Society journal.   Priyam Sinha is an Alexander Von Humboldt Postdoctoral Research Fellow at the Institute for Asian and African Studies, Humboldt University in Berlin. Her research interests lie at the intersection of critical media industry studies, disability studies, gender studies, affect studies, production culture studies, and anthropology of the body, and her work has been published in the European Journal of Cultural Studies, Media, Culture and Society; Communication, Culture and Critique; South Asian Diaspora, among others. She is also a regular podcast host at the New Books Network and has been published in public writing forums like the Economic and Political Weekly, FemAsia, Asian Film Archive, among others. More information on her ongoing projects can be found on her website and you can follow her on X. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/south-asian-studies

Around 2016, buoyed by so-called data kranti  ("data revolution"), an aspirational neo-middle class of users in India accessed internet for the first time on their mobile phones. Unlimited: Aspirational Politics and Mobile Media Distribution (MIT Press, 2026) tells the story of digital infrastructures that are being created by state-corporations for content and money to move and reach such users. It interrogates how their design impact the forms of inclusions and exclusions enacted as well as the horizon of social behaviors and expectations in "Digital India." The book contends that to understand the possibilities and limits of India's aspirational politics, media studies scholars should attend to infrastructures of aspiration: the distributional logistics of streaming content and mobile money are the infrastructural backbone that recalibrate thresholds of aspirational goals.  Digital content media distribution is also shaped by how user practices get entangled with particular affordances of platforms, and hence the need to study both participatory cultures of circulation and logistics of distribution together. Drawing on in-depth interviews, ethnographic fieldwork, critical discourse analysis and participant observation, the book traces the supply chains of content delivery networks enabling streaming video-on-demand services and informal ways of circulating "vernacular" music videos through memory cards. Unlimited does not restrict itself to formal media infrastructures, but also researches online phishing and lending scam assemblages to understand how such scams perform critical boundary work to reveal the cracks in and workings of financial distribution networks. This book offers a systematic examination of distribution considerations—including localization strategies—required for imagining mobile phone users across the varied regional geographies of "Digital India." Rahul Mukherjee is Associate Professor of TV & New Media and graduate chair in the Department of Cinema & Media Studies at University of Pennsylvania. His teaching and research focus on the logistical and environmental dimensions of digital infrastructures and platforms. Rahul is the author of the monograph Radiant Infrastructures, and his work has been published in Critical Inquiry, SM+S, New Media & Society, and Science, Technology & Human Values. He has co-edited a special issue on "Media Power in Digital Asia" for Media, Culture & Society journal.   Priyam Sinha is an Alexander Von Humboldt Postdoctoral Research Fellow at the Institute for Asian and African Studies, Humboldt University in Berlin. Her research interests lie at the intersection of critical media industry studies, disability studies, gender studies, affect studies, production culture studies, and anthropology of the body, and her work has been published in the European Journal of Cultural Studies, Media, Culture and Society; Communication, Culture and Critique; South Asian Diaspora, among others. She is also a regular podcast host at the New Books Network and has been published in public writing forums like the Economic and Political Weekly, FemAsia, Asian Film Archive, among others. More information on her ongoing projects can be found on her website and you can follow her on X. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/communications

Around 2016, buoyed by so-called data kranti  ("data revolution"), an aspirational neo-middle class of users in India accessed internet for the first time on their mobile phones. Unlimited: Aspirational Politics and Mobile Media Distribution (MIT Press, 2026) tells the story of digital infrastructures that are being created by state-corporations for content and money to move and reach such users. It interrogates how their design impact the forms of inclusions and exclusions enacted as well as the horizon of social behaviors and expectations in "Digital India." The book contends that to understand the possibilities and limits of India's aspirational politics, media studies scholars should attend to infrastructures of aspiration: the distributional logistics of streaming content and mobile money are the infrastructural backbone that recalibrate thresholds of aspirational goals.  Digital content media distribution is also shaped by how user practices get entangled with particular affordances of platforms, and hence the need to study both participatory cultures of circulation and logistics of distribution together. Drawing on in-depth interviews, ethnographic fieldwork, critical discourse analysis and participant observation, the book traces the supply chains of content delivery networks enabling streaming video-on-demand services and informal ways of circulating "vernacular" music videos through memory cards. Unlimited does not restrict itself to formal media infrastructures, but also researches online phishing and lending scam assemblages to understand how such scams perform critical boundary work to reveal the cracks in and workings of financial distribution networks. This book offers a systematic examination of distribution considerations—including localization strategies—required for imagining mobile phone users across the varied regional geographies of "Digital India." Rahul Mukherjee is Associate Professor of TV & New Media and graduate chair in the Department of Cinema & Media Studies at University of Pennsylvania. His teaching and research focus on the logistical and environmental dimensions of digital infrastructures and platforms. Rahul is the author of the monograph Radiant Infrastructures, and his work has been published in Critical Inquiry, SM+S, New Media & Society, and Science, Technology & Human Values. He has co-edited a special issue on "Media Power in Digital Asia" for Media, Culture & Society journal.   Priyam Sinha is an Alexander Von Humboldt Postdoctoral Research Fellow at the Institute for Asian and African Studies, Humboldt University in Berlin. Her research interests lie at the intersection of critical media industry studies, disability studies, gender studies, affect studies, production culture studies, and anthropology of the body, and her work has been published in the European Journal of Cultural Studies, Media, Culture and Society; Communication, Culture and Critique; South Asian Diaspora, among others. She is also a regular podcast host at the New Books Network and has been published in public writing forums like the Economic and Political Weekly, FemAsia, Asian Film Archive, among others. More information on her ongoing projects can be found on her website and you can follow her on X. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/science-technology-and-society

Around 2016, buoyed by so-called data kranti  ("data revolution"), an aspirational neo-middle class of users in India accessed internet for the first time on their mobile phones. Unlimited: Aspirational Politics and Mobile Media Distribution (MIT Press, 2026) tells the story of digital infrastructures that are being created by state-corporations for content and money to move and reach such users. It interrogates how their design impact the forms of inclusions and exclusions enacted as well as the horizon of social behaviors and expectations in "Digital India." The book contends that to understand the possibilities and limits of India's aspirational politics, media studies scholars should attend to infrastructures of aspiration: the distributional logistics of streaming content and mobile money are the infrastructural backbone that recalibrate thresholds of aspirational goals.  Digital content media distribution is also shaped by how user practices get entangled with particular affordances of platforms, and hence the need to study both participatory cultures of circulation and logistics of distribution together. Drawing on in-depth interviews, ethnographic fieldwork, critical discourse analysis and participant observation, the book traces the supply chains of content delivery networks enabling streaming video-on-demand services and informal ways of circulating "vernacular" music videos through memory cards. Unlimited does not restrict itself to formal media infrastructures, but also researches online phishing and lending scam assemblages to understand how such scams perform critical boundary work to reveal the cracks in and workings of financial distribution networks. This book offers a systematic examination of distribution considerations—including localization strategies—required for imagining mobile phone users across the varied regional geographies of "Digital India." Rahul Mukherjee is Associate Professor of TV & New Media and graduate chair in the Department of Cinema & Media Studies at University of Pennsylvania. His teaching and research focus on the logistical and environmental dimensions of digital infrastructures and platforms. Rahul is the author of the monograph Radiant Infrastructures, and his work has been published in Critical Inquiry, SM+S, New Media & Society, and Science, Technology & Human Values. He has co-edited a special issue on "Media Power in Digital Asia" for Media, Culture & Society journal.   Priyam Sinha is an Alexander Von Humboldt Postdoctoral Research Fellow at the Institute for Asian and African Studies, Humboldt University in Berlin. Her research interests lie at the intersection of critical media industry studies, disability studies, gender studies, affect studies, production culture studies, and anthropology of the body, and her work has been published in the European Journal of Cultural Studies, Media, Culture and Society; Communication, Culture and Critique; South Asian Diaspora, among others. She is also a regular podcast host at the New Books Network and has been published in public writing forums like the Economic and Political Weekly, FemAsia, Asian Film Archive, among others. More information on her ongoing projects can be found on her website and you can follow her on X. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/technology

Fluent Fiction - Hindi: Love Beyond Distance: A Night to Remember in Delhi Find the full episode transcript, vocabulary words, and more:fluentfiction.com/hi/episode/2026-06-01-22-34-01-hi Story Transcript:Hi: दिल्ली की रात थी।En: It was a night in Delhi.Hi: बत्ती मंद थी और दिल्ली का चकाचौंध वाला दृश्य खिड़की से नजर आ रहा था।En: The lights were dim, and the dazzling view of Delhi was visible from the window.Hi: आारव अपने लैपटॉप के सामने बैठा था।En: Aarav was sitting in front of his laptop.Hi: स्क्रीन पर एक डिजिटल स्क्रैपबुक खुली थी - उनकी और मनीषा की यादों का एक संग्राहलय।En: A digital scrapbook was open on the screen—a collection of memories of him and Manisha.Hi: आज उनकी सालगिरह थी, और वह मनीषा के लिए इस खास दिन को यादगार बनाना चाहता था।En: Today was their anniversary, and he wanted to make this special day memorable for Manisha.Hi: मनीषा लंदन में अपनी पढ़ाई में व्यस्त थी।En: Manisha was busy with her studies in London.Hi: उसके कमरे की छोटी खिड़की के पास एक पौधा रखा था, और किताबें चारों ओर बिखरीं थीं।En: A plant was placed near the small window of her room, and books were scattered all around.Hi: वह हर दिन बड़े सपने देखती थी, लेकिन उसके दिल का एक हिस्सा हमेशा दिल्ली में आारव के पास था।En: She dreamt big every day, but part of her heart was always with Aarav in Delhi.Hi: आारव का दोस्त राहुल भी उसके साथ था।En: Aarav's friend Rahul was also with him.Hi: राहुल उसे सलाह देता, "देख भाई, मनीषा के लिए कुछ ऐसा कर, जो उसे हमेशा याद रहे।En: Rahul advised him, "Look, brother, do something for Manisha that she will always remember."Hi: " आारव ने अपने मन की बात राहुल को कही, "मैं चाहता हूं कि मनीषा यह महसूस करे कि हमारा प्यार दिल से जुड़ा है, दूरी से नहीं।En: Aarav shared his thoughts with Rahul, "I want Manisha to feel that our love is connected by heart, not distance."Hi: "दिन और रात के समय अंतर से जूझते हुए, आारव ने योजना बनाई।En: Struggling with the time difference between day and night, Aarav made a plan.Hi: उसने सभी यादें और तस्वीरें स्क्रैपबुक में संजो दीं।En: He preserved all the memories and pictures in the scrapbook.Hi: फिर राहुल की मदद से एक वर्चुअल डिनर सेटअप किया।En: Then, with Rahul's help, he set up a virtual dinner.Hi: उसने सुनिश्चित किया कि जब मनीषा लॉग ऑन करे, उसे एक अनोखा सरप्राइज मिले।En: He ensured that when Manisha logged on, she would receive a unique surprise.Hi: शाम को जब मनीषा ने अपने लैपटॉप को खोला, तो उसे सिर्फ एक साधारण कॉल की उम्मीद थी।En: In the evening, when Manisha opened her laptop, she was only expecting a simple call.Hi: लेकिन जब उसने स्क्रीन पर आारव का बनाया हुआ डिजिटल स्क्रैपबुक देखा, उसकी आँखों में खुशी के आंसू आ गए।En: But when she saw the digital scrapbook created by Aarav on the screen, tears of joy came to her eyes.Hi: वीडियो कॉल के दूसरे किनारे पर एक खूबसूरती से सजा खाने की मेज थी - एक वर्चुअल डिनर।En: On the other side of the video call was a beautifully set dining table—a virtual dinner.Hi: आारव के चेहरे पर मुस्कान थी।En: Aarav had a smile on his face.Hi: उन्होंने ये मौका अपने साथ बिताए पुराने अच्छे समय को याद करते हुए बिताया।En: They spent this moment reminiscing about the good old times they had spent together.Hi: इस छोटी सी, लेकिन खास, वर्चुअल सैर ने उनके दिल को पहले से भी ज्यादा करीब ला दिया।En: This small yet special virtual journey brought their hearts closer than ever.Hi: कई समय जो उनकी मेहनत और कल्पना के कारण इसने एक नई चमक पाई।En: Many moments, because of their effort and imagination, found a new sparkle.Hi: आारव ने सीखा कि रिश्तों को मजबूत करने के लिए कोशिश और रचनात्मकता बहुत महत्वपूर्ण है।En: Aarav learned that effort and creativity are very important to strengthen relationships.Hi: इस प्रयास के बाद, उसे यह विश्वास हो गया कि चाहे मीलों की दूरी क्यों न हो, उनका प्यार हमेशा कायम रहेगा।En: After this endeavor, he was confident that no matter the distance in miles, their love would always endure.Hi: मनीषा ने भी महसूस किया कि प्यार समय और दूरी की सीमाओं से ऊपर है।En: Manisha also realized that love transcends the limits of time and distance.Hi: इस प्रकार वे अपने रिश्ते में पूरी तरह से आत्मविश्वास के साथ आगे बढ़े, जानते हुए कि उनके दिल हमेशा एक-दूसरे के करीब रहेंगे।En: Thus, they moved forward in their relationship with complete confidence, knowing that their hearts would always remain close to each other. Vocabulary Words:dim: मंदdazzling: चकाचौंधscrapbook: स्क्रैपबुकmemorable: यादगारanniversary: सालगिरहscattered: बिखरींadvised: सलाहstruggling: जूझतेpreserved: संजो दींvirtual: वर्चुअलunique: अनोखाexpected: उम्मीदreminiscing: यादendeavor: प्रयासstrengthen: मजबूतendure: कायमtranscends: ऊपरconfidence: आत्मविश्वासvisible: नजरcollection: संग्राहलयplaced: रखाdreamt: सपनेconnected: जुड़ाdifference: अंतरsetup: सेटअपlogged: लॉग ऑनsurprise: सरप्राइजtear: आंसूdining: खानेcreativity: रचनात्मकता

Fluent Fiction - Hindi: Santorini Secrets: Unearthing the Jewel of Greek Legends Find the full episode transcript, vocabulary words, and more:fluentfiction.com/hi/episode/2026-05-30-07-38-19-hi Story Transcript:Hi: संतोरिनी के रंगीन मौसम में, नीले गिरजे और सफेद इमारतों के बीच, आरव, ईशिता और राहुल अपनी छुट्टियाँ बिता रहे थे।En: In the colorful season of Santorini, amidst the blue churches and white buildings, Aarav, Ishita, and Rahul were spending their vacation.Hi: ये वसंत काल था और ग्रीस का प्रसिद्ध ऑर्थोडॉक्स ईस्टर उत्सव मनाया जा रहा था।En: It was springtime, and the famous Greek Orthodox Easter festival was being celebrated.Hi: चारों तरफ लोग उल्लासित थे, हर कोने में रंग-बिरंगी सजावट थी।En: Everywhere people were joyful, with colorful decorations in every corner.Hi: आरव, हमेशा की तरह, अपनी साहसिक प्रवृति के चलते कुछ नया खोजने की चाह में था।En: Aarav, as always, had a desire to discover something new due to his adventurous nature.Hi: ईशिता, उसकी साथी, सतर्क और व्यावहारिक थी।En: Ishita, his companion, was cautious and practical.Hi: उसे रहस्यों में कभी विश्वास न था।En: She never believed in mysteries.Hi: वही राहुल, एक स्वप्नदर्शी, हर घटना में रोमांच खोजने का प्रयास करता था।En: Rahul, on the other hand, a dreamer, tried to find excitement in every incident.Hi: उनकी छुट्टियों का आनंद एक अजीब घटना से बाधित हो गया।En: Their vacation enjoyment was interrupted by a strange event.Hi: आरव के परिवार की एक पुरानी विरासत, एक खूबसूरत गहना, अचानक गायब हो गया।En: An old family heirloom of Aarav, a beautiful jewel, suddenly went missing.Hi: आरव ने पहले तो इसे अनचाही मुसीबत समझा।En: Initially, Aarav thought of it as an unwanted hassle.Hi: लेकिन जल्दी ही इस रहस्य में उसकी रुचि बढ़ने लगी।En: But soon, his interest in this mystery began to grow.Hi: स्थानीय लोग इस विरासत के बारे में किसी भी तरह की जानकारी साझा करने से बच रहे थे।En: The local people were avoiding sharing any information about this heirloom.Hi: ईशिता चिंतित थी कि इस मामले में उलझना उन्हें परेशानी में डाल सकता है।En: Ishita was worried that getting involved in this matter might cause them trouble.Hi: आरव ने उसके चिंताओं को नज़रअंदाज़ कर, स्थानीय पुरानी कथाओं को खंगालने का निश्चय कर लिया।En: Ignoring her concerns, Aarav decided to delve into the local ancient tales.Hi: शाम की सुनहरी रोशनी में, आरव ने राहुल के साथ मिलकर पुराने दस्तावेजों और कहानियों का अध्ययन किया।En: In the golden evening light, Aarav and Rahul together studied old documents and stories.Hi: इसी दौरान, उन्हें अपनी हवेली के नीचे एक गुप्त कक्ष होने का पता चला।En: During this, they discovered a secret chamber beneath their mansion.Hi: कहानियों के अनुसार, इस कक्ष में बहुत से गुप्त रहस्य छिपे थे।En: According to the stories, many hidden secrets were concealed in this chamber.Hi: कक्ष में पहुँचकर, उन्होंने देखा कि बीच में एक पत्थर का बक्सा रखा था।En: Upon reaching the chamber, they saw that a stone box was placed in the middle.Hi: आरव का दिल तेजी से धड़कने लगा।En: Aarav's heart started beating rapidly.Hi: बक्से को खोलने पर, उसमें उसी विरासत का गहना सुरक्षित रखा मिला।En: Upon opening the box, the same heirloom jewel was found safely kept inside.Hi: साथ में, कुछ पुराने दस्तावेज भी थे, जो गहने की ऐतिहासिक और सांस्कृतिक महत्ता के बारे में बताते थे।En: Along with it, there were some old documents describing the jewel's historical and cultural significance.Hi: इस खोज ने न केवल आरव की जिज्ञासा को तृप्त किया, बल्कि उसे यह भी सिखाया कि अनजाने रहस्यों के पीछे छिपी हुई गहराईयों का सम्मान करना कितना महत्वपूर्ण है।En: This discovery not only satisfied Aarav's curiosity but also taught him the importance of respecting the depths hidden behind unknown mysteries.Hi: उसने वह जानकारी स्थानीय लोगों के साथ साझा की।En: He shared this information with the local people.Hi: अब, ना केवल विरासत सुरक्षित थी, बल्कि वह कहानी भी सबके सामने थी।En: Now, not only was the heirloom safe, but the story was also out in the open.Hi: कहानी का अंत हुआ तो आरव ने सांतोरीनी के अद्वितीय परंपराओं की और गहरी समझ पा ली।En: As the story ended, Aarav gained a deeper understanding of Santorini's unique traditions.Hi: अब वह दूसरों की संस्कृति और उनकी कहानियों के प्रति और अधिक सम्मानित था।En: He now held more respect for the culture and stories of others.Hi: यह यात्रा उनके लिए एक अद्भुत अनुभव साबित हुई और वे यादों के साथ अपने घर लौट आए।En: This trip proved to be an amazing experience for them, and they returned home with memories. Vocabulary Words:colorful: रंगीनvacation: छुट्टियाँcelebrated: मनाया जा रहा थाadventurous: साहसिकcautious: सतर्कpractical: व्यावहारिकdreamer: स्वप्नदर्शीheirloom: विरासतmystery: रहस्यhassle: मुसीबतdelve: खंगालनेchamber: कक्षconcealed: छिपेdocuments: दस्तावेज़significance: महत्ताcuriosity: जिज्ञासाrespecting: सम्मानtraditions: परंपराओंincident: घटनाcompanion: साथीinterrupted: बाधितavoiding: बच रहेconcerns: चिंताओंgolden: सुनहरीrapidly: तेजीanalyze: अध्ययनbeneath: नीचेsatisfied: तृप्तhidden: छिपीunique: अद्वितीय

கேள்விகளை எதிர்கொள்ளத் தயங்குகிறாரா முதலமைச்சர் விஜய்?ஓசூர், கோயம்புத்தூர், மதுரைக்கு மெட்ரோ - வேறு என்ன கோரிக்கை? நிர்மலா சீதாராமன் - விஜய் சந்திப்பு!ராகுல் காந்தியை சந்திக்காமல் சென்னை புறப்படும் விஜய்?"அமலாக்கத்துறை சோதனை குறித்து விஜய் பேச வேண்டும்" - CPM கட்சியின் ஜி.செல்வா பேட்டி பரந்தூர் விமான நிலைய திட்டம் கைவிடப்படுகிறதா?ரீல்ஸ் போடும் தொழில்துறை அமைச்சர்? சிங்கப்பெண் திட்டத்துக்கு சீருடை அறிமுகம்? தனியாக ஆலோசனை நடத்துவது ஏன்? சி.விஜயபாஸ்கர் விளக்கம்தவெகவில் இணைந்தார் வெல்லமண்டி நடராஜன்!நமது அம்மா நாளிதழில் மீண்டும் எடப்பாடி பழனிசாமியின் பெயர் நிறுவனராக சேர்ப்பு!ஒரு மாதத்தில் 90% அதிமுக நிர்வாகிகள், தவெகவுக்கு வருவார்கள் - ஆதவ் அர்ஜுனாசித்தராமையா காலில் விழுந்து ஆசீர்வாதம் வாங்கினார் டி.கே.சிவகுமார். ராகுலுக்கு இப்போது மகிழ்ச்சியாக இருக்கும் - பினராயி விஜயன்ட்ரம்ப் போல் தோற்றமளிக்கும் எருமையை மீட்டு தேசிய உயிரியல் பூங்காவிற்கு அனுப்பி வைத்த வங்கதேச அரசு. புனே: குடிபோதையில் கார் ஏற்றி இருவரைக் கொன்ற சிறுவன்; மகனின் ஜாமீனை ஆடிப்பாடி கொண்டாடிய தந்தைபைஜூஸ் நிறுவனருக்கு 6 மாதம் சிறை... ஏன்?

This week, Michelle, Rahul and Will explore prediction markets — online platforms where people can bet on future events, from elections to pop culture and even world conflicts.Concerns about insider trading are on the rise and platforms are being banned in an increasing number of countries. So as talk of regulation increases, we try to predict the future of the prediction market.Presenters: Michelle Fleury, Rahul Tandon and Will BainProducer: Rebecca Smyllie(Photo: Getty/Yuichiro Chino)

Fluent Fiction - Hindi: Unveiling History: A Journey Through Hampi's Hidden Gems Find the full episode transcript, vocabulary words, and more:fluentfiction.com/hi/episode/2026-05-27-22-34-01-hi Story Transcript:Hi: वसंत का मौसम था।En: It was the spring season.Hi: हम्पी के प्राचीन खंडहर अपनी शान में खड़े थे।En: The ancient ruins of Hampi stood in their grandeur.Hi: नीला आकाश साफ था, और धूप पत्थरों पर हल्की चमक बिखेर रही थी।En: The blue sky was clear, and sunlight cast a gentle glow on the stones.Hi: पुरानी कहानियाँ इन शिलाओं में छिपी थीं।En: Old stories were hidden within these rocks.Hi: यात्री इन कहानियों की थ्रेड्स की तरह रेतीली पगडंडियों पर घूम रहे थे।En: Travelers wandered the sandy paths like threads of these stories.Hi: अनया, एक साहसी यात्री, इतिहास से अपनापन महसूस करती थी।En: Anaya, an adventurous traveler, felt a connection with history.Hi: राहुल, उसका दोस्त, आधुनिक सुख-सुविधाओं में रुचि रखता था।En: Rahul, her friend, was interested in modern comforts.Hi: अनया को एक दुर्लभ वस्तु की तलाश थी जो उसे हम्पी के इतिहास से जोड़ सके।En: Anaya was looking for a rare item that could connect her to the history of Hampi.Hi: "चलो, जल्दी चलते हैं," राहुल ने कहा।En: "Come on, let's move quickly," Rahul said.Hi: "यहां ज्यादा समय मत लगाना, हमें समय पर होटल पहुँचना है।En: "Don't take too long here, we need to reach the hotel on time."Hi: "अनया ने सिर हिलाया, पर उसका मन कहीं और था।En: Anaya nodded, but her mind was elsewhere.Hi: कुछ तो था यहाँ जो उसे खींच रहा था।En: There was something here that was drawing her.Hi: उसने एक पल सोचा, और फिर फैसला किया।En: She thought for a moment and then made a decision.Hi: "मैं थोड़ी देर में आती हूं," उसने कहा।En: "I'll be back in a little while," she said.Hi: अनया भीड़ से दूर एक छोटी सी पगडंडी की तरफ चल पड़ी।En: Anaya walked toward a small path away from the crowd.Hi: पीठ के पीछे राहुल की हल्की नाराज़गी उसे सुनाई दी, पर उसने परवाह नहीं की।En: She could hear Rahul's slight annoyance behind her, but she didn't care.Hi: वह जानती थी कि उसे क्या चाहिए।En: She knew what she needed.Hi: यहां एक छोटी सी दुकान थी।En: There was a small shop here.Hi: दुकान में प्राचीन दिखने वाले छोटे ट्रिंकिट्स रखे थे।En: The shop had small ancient-looking trinkets.Hi: अनाय की नजर एक ख़ास सजावटी पत्थर पर पड़ी।En: Anaya's eyes fell on a particular decorative stone.Hi: यह पत्थर ऐसे लग रहा था जैसे समय की परतों में से गुज़रकर आया हो।En: This stone looked as if it had traveled through layers of time.Hi: उसकी आँखों में चमक आ गई।En: Her eyes sparkled.Hi: "आपको पसंद है?En: "Do you like it?"Hi: " दुकानदार ने पूछा।En: the shopkeeper asked.Hi: "हाँ, यह खास है," अनया ने मुस्कुराते हुए कहा।En: "Yes, it is special," Anaya said with a smile.Hi: उसने पत्थर ख़रीद लिया।En: She bought the stone.Hi: जब वह वापस लौटी, राहुल ने पत्थर को देखा।En: When she returned, Rahul saw the stone.Hi: "यह कौन सा पत्थर है?En: "What kind of stone is this?"Hi: " उसने पूछा।En: he asked.Hi: "यह इतिहास की एक कड़ी है," अनया ने कहा।En: "This is a link to history," Anaya said.Hi: उसने राहुल को पत्थर की कहानी सुनाई।En: She told Rahul the story of the stone.Hi: सुनते-सुनते राहुल की आँखों में भी रुचि जाग गई।En: As he listened, interest sprouted in Rahul's eyes as well.Hi: अनया अपने निर्णय से संतुष्ट थी।En: Anaya was satisfied with her decision.Hi: अब वह इतिहास को और भी गहराई से समझती थी।En: Now she understood history even more deeply.Hi: और राहुल?En: And Rahul?Hi: वह अब संस्कृति की खोज में दिलचस्पी लेने लगा था।En: He now began to take an interest in exploring culture.Hi: इतिहास की ओर झुकाव कभी-कभी छुपे हुए रत्न मिलते हैं।En: A leaning towards history sometimes uncovers hidden gems.Hi: हम्पी के खंडहर अब उनके बीच एक सेतु बन चुके थे।En: The ruins of Hampi had now become a bridge between them.Hi: और वे दोनों इस यादगार यात्रा से, एक नई दृष्टि के साथ वापस लौटे।En: And they both returned from this memorable journey with a new perspective.Hi: कहानी समाप्त हुई, लेकिन उनकी खोज अब शुरू हुई थी।En: The story ended, but their quest had just begun. Vocabulary Words:ancient: प्राचीनruins: खंडहरgrandeur: शानglow: चमकstones: पत्थरोंwandering: घूम रहे थेadventurous: साहसीtraveler: यात्रीconnection: अपनापनmodern comforts: आधुनिक सुख-सुविधाएंrare: दुर्लभitem: वस्तुintrigued: जिज्ञासुannoyance: नाराज़गीcrowd: भीड़trinkets: छोटे ट्रिंकिट्सdecorative: सजावटीlayers: परतोंsparkled: चमकshopkeeper: दुकानदारlink: कड़ीinterest: रुचिsatisfied: संतुष्टuncover: मिलतेhidden: छुपे हुएgems: रत्नbridge: सेतुperspective: दृष्टिmemorable: यादगारquest: खोज

Fluent Fiction - Hindi: From Village to Victory: Finding Roots in the Urban Jungle Find the full episode transcript, vocabulary words, and more:fluentfiction.com/hi/episode/2026-05-23-07-38-19-hi Story Transcript:Hi: शहर की चकाचौंध में तन्हा सफर कर रहा था अर्जुन।En: In the dazzle of the city, Arjun was traveling alone.Hi: ऊँची इमारतें, भीड़ भरी सड़कें, और अनंत दौड़-धूप ने उसे गाँव के शांत माहौल से जैसे बहुत दूर ला दिया था।En: Tall buildings, crowded streets, and the endless hustle and bustle felt as if they had taken him far away from the peaceful environment of his village.Hi: वसंत का मौसम था, पेड़ फूलों से लदे थे, पर अर्जुन के मन का उदासीन सन्नाटा उन्हें महसूस भी नहीं कर पाता था।En: It was spring, the trees were laden with flowers, but the indifferent silence in Arjun's mind couldn't even feel them.Hi: अर्जुन छोटे से गाँव से आया था।En: Arjun came from a small village.Hi: वहाँ के हरे-भरे खेत, साफ हवा, और अपने परिवार का प्यार उसके दिल के बहुत करीब था।En: The green fields, fresh air, and family love there were very close to his heart.Hi: लेकिन शहर के इस जंगल में वह अकेला पड़ गया था।En: But in this jungle of the city, he found himself alone.Hi: उसे लगता था कि इस भीड़ में उसका कोई नहीं है।En: He felt as if, in this crowd, he had no one of his own.Hi: वह सबके बीच होकर भी अकेला था।En: Even among everyone, he was lonely.Hi: रोज़मर्रा की ज़िंदगी में खोए-खोए अर्जुन की मुलाकात अंतिम बार अपने बचपन के दोस्त राहुल से हुई।En: Lost in the routine of daily life, Arjun met his childhood friend Rahul for the last time.Hi: राहुल ने उसे अपने साथ एक स्थानीय सांस्कृतिक कार्यक्रम में चलने का निमंत्रण दिया।En: Rahul invited him to join a local cultural event.Hi: पहले तो अर्जुन हिचकिचाया, पर फिर सोचा कि शायद इसी बहाने कुछ नया सीखने और देखने को मिलेगा।En: Initially, Arjun hesitated, but then thought that maybe he would get to learn and see something new.Hi: कार्यक्रम की शाम, अर्जुन ने देखा कि कितनी विविधता और रंगीनियाँ इस शहर में हैं।En: On the evening of the event, Arjun saw how diverse and colorful this city is.Hi: जब सब लोग अपने पारंपरिक परिधान पहनकर नाच रहे थे, गा रहे थे, तो अर्जुन को महसूस हुआ कि वह भी तो उन्हीं में से एक है।En: When everyone was dancing and singing in their traditional attire, Arjun felt that he was one of them too.Hi: उसे घर की याद आ रही थी, पर अपने परिवार से बात करके उसका मन कुछ हल्का हो गया।En: He missed home, but talking to his family lightened his heart a bit.Hi: वहीं, उसे सीता मिली।En: There, he met Sita.Hi: सीता वहीं के एक लोकल समुदाय की प्रमुख थी जो गाँव से आने वाले लोगों की मदद करती थी।En: Sita was a leader of a local community who helped people coming from villages.Hi: उन्होंने अर्जुन को अपने ग्रुप से जुड़ने का निमंत्रण दिया।En: She invited Arjun to join her group.Hi: अर्जुन ने सोचा कि यही वह मौका है जहाँ उसे अपने भीतर का अस्तित्व खोजने में मदद मिल सकती है।En: Arjun thought that this was the opportunity where he could find help in discovering his inner existence.Hi: कार्यक्रम के दौरान, जब सबने मिलकर एक लोक नृत्य किया, तो अर्जुन के चेहरे पर मुस्कान आई।En: During the program, when everyone performed a folk dance together, a smile appeared on Arjun's face.Hi: उसे अहसास हुआ कि वह जहाँ है, वहाँ भी अपनी जड़ों से जुड़ा रह सकता है।En: He realized that even here, he could stay connected to his roots.Hi: उसे लगा जैसे उसकी आत्मा को एक नया संबल मिला हो।En: It felt as though his soul had found a new strength.Hi: लौटते समय वह शांत था, मानो उसके सभी प्रश्नों के उत्तर मिल गए हों।En: On his way back, he was calm, as if he had found answers to all his questions.Hi: उसे विश्वास था कि वह इस शहर में अपनी पहचान जरूर बना लेगा।En: He was confident that he would certainly make his identity in this city.Hi: शायद उसने सीख लिया था कि जड़ें कभी नहीं छूटतीं; वे हमेशा हमारे साथ रहती हैं।En: Perhaps he had learned that roots never leave; they always stay with us.Hi: अर्जुन अब अपने भविष्य को लेकर आश्वस्त था और शहर की चुनौतीभरी जिंदगी को खुले दिल से स्वीकार करने के लिए तैयार था।En: Arjun was now confident about his future and ready to embrace the challenging life of the city with an open heart.Hi: उसके चेहरे पर आत्मविश्वास की झलक थी, और यही सही मायनों में उसकी जीत थी।En: There was a glimpse of confidence on his face, and this was truly his victory. Vocabulary Words:dazzle: चकाचौंधladen: लदेindifferent: उदासीनtranquility: शांत माहौलsolitary: तन्हाfoliage: हरा-भरा खेतamidst: बीचhesitated: हिचकिचायाdiverse: विविधताattire: परिधानcherished: करीबsustenance: संबलopportunity: मौकाcommunity: समुदायinvite: निमंत्रणperspective: आश्वस्तidentity: पहचानembrace: स्वीकारroutine: रोज़मर्रा की ज़िंदगीdance: नृत्यstrength: मजबूतीglimpse: झलकvictory: जीतcalm: शांतinhabitants: लोगexistence: अस्तित्वroots: जड़ेंconcept: अहसासperform: कियाlocal: स्थानीय

Rahul Vorra is the founder and CEO of Superhuman, the premium email client for power users. He previously built the Gmail plug-in Reportive and sold it to LinkedIn. He began somewhere unexpected though, as a game designer on RuneScape. In this conversation, Rahul breaks down why most founders misunderstand product market fit, why premium can actually hurt your business, and how deliberate constraint can become your biggest advantage.   Follow Rahul Vohra on X: https://x.com/rahulvohra Follow Fareed Mosavat on X: https://x.com/far33d Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Suvendu Masterstrokes & Meltdown | Yogi get's Ready for UP | Rahul vs Priyanka | Karan Verma

Ben Pruitt is back with a Brand New Season of Bending Not Breaking Featuring Co-Hosts from Across the BNB Patreon Community! This Week : Ben is joined by returning Patrons Kelly, Maggie, & Rahul to discuss The Legend of Korra S1E8 : When Extremes Meet, through the Lens of INTIMIDATION. Follow : @bnb_pod & @thearkofenetwork on Instagram Music : "The Demon Way" by nARK Produced By Noah Blanchard Released By The ARK of E Network Send Feedback : thearkofe@gmail.com

How do you help 7500 co-workers be their most creative selves? Find out in the latest Ad Infinitum.That's right, the world's only podcast solely dedicated to audio ads is back! Presenting Ad Infinitum Season 4, Episode 2: "Rahul Sabnis: Guaranteed Human."Host Stew Redwine (Executive Creative Director, Oxford Road) welcomes bona fide creative master Rahul Sabnis (President & Chief Creative Officer, iHeartMedia) for a WIDE-ranging conversation spanning: Picking a Side, Creativity for All, The Memory Test, and more. There's even an Audiolytics breakdown of ads from Mint Mobile, Aura Frames, Toyota, and Amazon Prime. Let's dig in…“A voice in the dark when you feel alone.” -The purpose of radio, according to Rahul Sabnis (President & Chief Creative Officer, iHeartMedia)See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Synopsis: At the intersection of personal mission and biotech leadership, Rahul Chaturvedi sits down with Catherine Owen Adams, CEO of Acadia Pharmaceuticals, for a deeply personal and strategically rich conversation on leadership, commercialization, and the future of neuropsychiatry. From starting as a pharmacist in the UK to pivoting from R&D into commercial leadership at Johnson & Johnson, rising through Bristol Myers Squibb, and ultimately stepping into her first biotech CEO role at Acadia, Catherine shares how storytelling became the throughline of her career—transforming science into physician trust, investor conviction, and enterprise vision. In this episode, Catherine opens up about the personal family experiences with neurodegenerative disease that made Acadia's focus on CNS and rare disease feel like her “Goldilocks opportunity.” She offers a candid look at the realities of being a first-time CEO, managing investor ecosystems, building the right C-suite, balancing billion-dollar commercial execution with high-risk R&D, and navigating the emotional stakes of developing therapies for Parkinson's disease psychosis, Alzheimer's disease psychosis, Rett syndrome, and beyond. Rahul and Catherine also explore the seismic shifts reshaping biotech—from AI-powered commercialization and patient services to policy advocacy through BIO, FDA modernization, and the strategic pressures facing CNS innovation. This episode is both a masterclass in biotech leadership and a powerful reminder that the best CEOs don't just run companies—they tell stories that move science, markets, and patients forward. Biography: Ms. Owen Adams joined Acadia as Chief Executive Officer and as a member of our Board of Directors in September 2024. Ms. Owen Adams has over 25 years of executive level experience in the pharmaceutical industry. Prior to joining Acadia, Ms. Owen Adams served as Senior Vice President and General Manager, U.S., at Bristol Myers Squibb (BMS), where she led a $20 billion commercial business, overseeing a large and diverse portfolio of promoted brands across Oncology, Cardiovascular, and Immunology. Previously, Ms. Owen Adams held the position of Senior Vice President, Head of Major Markets at BMS, where she led commercial operations leading 6,000 employees across 19 countries in Europe, Japan, and Canada during BMS's merger with Celgene. Prior to her tenure at BMS, Ms. Owen Adams spent 25 years at Johnson & Johnson (J&J), where she held leadership roles across global, U.S., and European business units, with her last position being President, Janssen Immunology U.S. Ms. Owen Adams began her career in R&D and manufacturing at AstraZeneca. Ms. Owen Adams currently serves on the board of directors of Agios Pharmaceuticals, Inc., a publicly held company, and AssistRx, a privately held company. Ms. Owen Adams was formerly on the board of directors and chair of the compensation committee for Optinose PLC, a public specialty pharmaceutical company, and was on the board of directors of Robert Wood Johnson University Hospitals, a non-profit organization. Ms. Owen Adams earned a BSc. in Pharmacy from the University of Manchester, becoming a qualified pharmacist and member of the Royal Pharmaceutical Society (MRPhS).

Superhuman Mail users respond to 72% more emails per hour and save an average of four hours every week — numbers backed by a case study from one of the Big Three strategy consulting firms. Rahul Vohra, CEO at Superhuman Mail, built the world's fastest email engine over three years without launching, held the line until the product was ready, and then productized product-market fit into a repeatable, measurable science. Following Superhuman's acquisition by Grammarly in 2025, Rahul is now steering the company toward a unified AI-native productivity suite spanning email, calendar, tasks, and agents.What you'll learn:The 5-step PMF Engine: how to survey, segment, analyze, implement, and track your way to product-market fit with a numerical scoreWhy you should ignore the not disappointed and most somewhat disappointed users — and which signals actually tell you who to build forHow to use the High Expectation Customer (HXC) framework to narrow your market without changing your productWhy PMF is a moving target and how to defend it against commoditization and copy-cat competitionHow Rahul operates as the editor of the product — using 20 verbatim quotes to push PMs and designers to sharper decisionsKey takeaways:If more than 40% of your users would be very disappointed without your product, you have an initial PMF — and you can measure your way thereChanging your market is faster than changing your product — segmentation alone can jump your PMF score 10 points overnightBuilding for your highest-expectation customer is not the same as building for your ICP — confuse the two, and you'll optimize for the wrong signalCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Rahul VohraSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Welcome to another episode of the Oncology Brothers podcast! In this episode, hosts Rahul and Rohit Gosain dive deep into the treatment algorithms for early-stage non-small cell lung cancer (NSCLC) with curative intent. Joined by leading thoracic medical oncologist Dr. Sanjay Popat from London, they discussed the critical role of next-generation sequencing (NGS) in treatment planning, the importance of proper staging, and the implications of actionable mutations. Listen us on: Spotify: https://open.spotify.com/show/31BXhY9FM4gPWG10WgE11o Apple Podcast: https://podcasts.apple.com/us/podcast/oncology-brothers-practice-changing-cancer-discussions/id1653340966 Follow us on social media: X/Twitter: https://twitter.com/oncbrothers ⁠Instagram: https://www.instagram.com/oncbrothers Website: https://oncbrothers.com/ Key topics covered included: The significance of NGS testing and its impact on treatment decisions. Insights from the CHECKMATE 816 trial, highlighting the benefits of neoadjuvant chemoimmunotherapy. The complexities of post-operative immunotherapy and patient-shared decision-making. The role of adjuvant chemotherapy in patients with actionable mutations like EGFR and ALK. The latest data on osimertinib and alectinib in the adjuvant setting. The standard of care for unresectable disease based on the PACIFIC trial and the implications of PD-L1 status. Join us for an informative discussion that unpacks the latest advancements in NSCLC treatment and emphasizes the importance of personalized care. Don't forget to subscribe for more episodes in our treatment algorithm series! #EarlyStageNSCLC, #CHECKMATE816, #NeoadjuvantTherapy, #PrecisionMedicine, #OncologyBrothers

Ben Pruitt is back with a Brand New Season of Bending Not Breaking Featuring Co-Hosts from Across the BNB Patreon Community! This Week : Ben is joined by returning Patrons Kelly, Maggie, & Rahul to discuss The Legend of Korra S1E7 : The Aftermath, through the Lens of AFTERSHOCK. Follow : @bnb_pod & @thearkofenetwork on Instagram Music : "Corporeal" & "amdistor" by nARK Produced By Noah Blanchard Released By The ARK of E Network Send Feedback : thearkofe@gmail.com