Podcasts about clarifai

The United States has imposed new export restrictions on 140 Chinese companies to curb advancements in semiconductors, particularly in AI and military applications, potentially disrupting the global supply chain and increasing costs across industries. This move has sparked criticism from China's Commerce Ministry and highlights ongoing geopolitical tensions. Google's AI video generator, Veo, will soon be available for private preview on Google Cloud's Vertex AI, enabling clients like Quora and Mondelez International to create high-definition video content. Google is addressing ethical and legal concerns related to AI-generated content and intellectual property rights. Vishnu Mohandas, after leaving Google over privacy concerns, created Ente, a secure, end-to-end encrypted photo storage service prioritizing user privacy. Ente has gained over 100,000 users, offering a trustworthy alternative for those concerned about data security. Alfonso Cobo launched Hypelist, an app transforming traditional list-making into a visually appealing and user-friendly experience, integrating AI chatbots for personalized recommendations and fostering community collaboration. OpenAI has appointed Kate Rouch as its first Chief Marketing Officer to enhance brand recognition and trust, focusing on promoting capabilities, ensuring ethical leadership, and leveraging strategic partnerships. Britain's National Cyber Security Centre reports a 16% rise in cyber incidents in 2024, with increasing sophistication of attacks leveraging AI, prompting advanced defense strategies and international collaborations. Clarifai launched a vendor-agnostic AI life cycle platform to revolutionize the orchestration, management, and optimization of computational resources for enterprise and government customers, marking a shift to more commercially viable and ethically sound AI applications.

SummaryIn this episode we're joined by Matt Zeiler, founder and CEO of Clarifai, as he dives into the technical aspects of retrieval augmented generation (RAG). From his journey into AI at the University of Toronto to founding one of the first deep learning AI companies, Matt shares his insights on the evolution of neural networks and generative models over the last 15 years. He explains how RAG addresses issues with large language models, including data staleness and hallucinations, by providing dynamic access to information through vector databases and embedding models. Throughout the conversation, Matt and host Tobias Macy discuss everything from architectural requirements to operational considerations, as well as the practical applications of RAG in industries like intelligence, healthcare, and finance. Tune in for a comprehensive look at RAG and its future trends in AI.AnnouncementsHello and welcome to the AI Engineering Podcast, your guide to the fast-moving world of building scalable and maintainable AI systemsYour host is Tobias Macey and today I'm interviewing Matt Zeiler, Founder & CEO of Clarifai, about the technical aspects of RAG, including the architectural requirements, edge cases, and evolutionary characteristicsInterviewIntroductionHow did you get involved in the area of data management?Can you describe what RAG (Retrieval Augmented Generation) is?What are the contexts in which you would want to use RAG?What are the alternatives to RAG?What are the architectural/technical components that are required for production grade RAG?Getting a quick proof-of-concept working for RAG is fairly straightforward. What are the failures modes/edge cases that start to surface as you scale the usage and complexity?The first step of building the corpus for RAG is to generate the embeddings. Can you talk through the planning and design process? (e.g. model selection for embeddings, storage capacity/latency, etc.)How does the modality of the input/output affect this and downstream decisions? (e.g. text vs. image vs. audio, etc.)What are the features of a vector store that are most critical for RAG?The set of available generative models is expanding and changing at breakneck speed. What are the foundational aspects that you look for in selecting which model(s) to use for the output?Vector databases have been gaining ground for search functionality, even without generative AI. What are some of the other ways that elements of RAG can be re-purposed?What are the most interesting, innovative, or unexpected ways that you have seen RAG used?What are the most interesting, unexpected, or challenging lessons that you have learned while working on RAG?When is RAG the wrong choice?What are the main trends that you are following for RAG and its component elements going forward?Contact InfoWebsiteLinkedInParting QuestionFrom your perspective, what is the biggest barrier to adoption of machine learning today?Closing AnnouncementsThank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. [Podcast.__init__]() covers the Python language, its community, and the innovative ways it is being used.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email hosts@aiengineeringpodcast.com with your story.To help other people find the show please leave a review on iTunes and tell your friends and co-workers.LinksClarifaiGeoff HintonYann LecunNeural NetworksDeep LearningRetrieval Augmented GenerationContext WindowVector DatabasePrompt EngineeringMistralLlama 3Embedding QuantizationActive LearningGoogle GeminiAI Model AttentionRecurrent NetworkConvolutional NetworkReranking ModelStop WordsMassive Text Embedding Benchmark (MTEB)Retool State of AI ReportpgvectorMilvusQdrantPineconeOpenLLM LeaderboardSemantic SearchHashicorpThe intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0

In episode 15 of Venture Everywhere, Sylvia Kuyel, founding partner at Fund XX as part of Everywhere VC, interviews Liz O'Sullivan, founder and CEO at Vera, a startup leader and AI advocate advising early and mid-stage companies on Artificial Intelligence design practices, strategies, and product development. Liz discusses her startup experience and her mission to promote responsible AI. She highlights the unpredictable nature of AI and the necessity for human oversight. Liz also addresses challenges in scaling teams and fostering inclusivity in remote work environments. She believes AI can advance science but stresses the importance of governance and policies to protect marginalized communities.In this episode, you will hear:The importance of being practical and realistic about the capabilities and limitations of AI, as well as the need for human control over its use.Vera as a gateway for companies looking to deploy AI and to foster its adoption while reducing risks.Potential benefits and risks of AI, including job automation, bias, and the transformation of various industries.Liz's personal journey in the AI field, including her work at Clarifai and her decision to leave a job involving military applications of AI.The importance of understanding both the long-term risks and the immediate risks of AI, and the need for collaboration and compromise within the AI community.Find Liz O'Sullivan at:Website: https://www.askvera.io/LinkedIn: linkedin.com/in/lizzosullivanLearn more about Sylvia and The Fund XX:Website: https://everywhere.vc/LinkedIn: linkedin.com/in/sylvia-kuyel-3aa1803Twitter: https://twitter.com/skuyelIf you liked this episode, please give us a rating wherever you found us. To learn more about our work, visit Everywhere.vc and subscribe to our Founders Everywhere Substack. You can also follow us on LinkedIn and Twitter for regular updates and news.

Josh Wolfe co-founded Lux Capital to support scientists and entrepreneurs who pursue counter-conventional solutions to the most vexing puzzles of our time in order to lead us into a brighter future. The more ambitious the project, the better—like, say, creating matter from light. Wolfe is a director at Shapeways, Strateos, Lux Research, Kallyope, CTRL-labs, Variant, and Varda, and helped lead Lux Capital's investments in Anduril, Planet, Echodyne, Clarifai, Authorea, Resilience, and Hadrian. He is a founding investor and board member with Bill Gates in Kymeta, which makes cutting-edge antennas for high-speed global satellite and space communications. In this presentation, Wolfe shares the principles that guide his entrepreneurship and investments, giving examples from companies he has founded and funded.

Synopsis: Josh Wolfe is the Co-Founder and Managing Partner of Lux Capital, a venture capital firm that invests in emerging science and technology ventures. Josh joins us for a discussion centered around investing in biotech. He discusses the arc of his career and the forces that led him to pursue a path at the intersection of science and finance. Josh also talks about the current state of biotech investing, trends he expects to see in the future, his advice to founder-led biotech companies, what he believes are the top three criteria for success for biotech companies, and his thoughts on the future of biotech. It's an illuminating conversation you won't want to miss. Biography: Josh co-founded Lux Capital to support scientists and entrepreneurs who pursue counter-conventional solutions to the most vexing puzzles of our time in order to lead us into a brighter future. The more ambitious the project, the better—like, say, creating matter from light. Josh is a Director at Shapeways, Strateos, Lux Research, Kallyope, CTRL-labs, Variant, and Varda, and helped lead the firm's investments in Anduril, Planet, Echodyne, Clarifai, Authorea, Resilience and Hadrian. He is a founding investor and board member with Bill Gates in Kymeta, making cutting-edge antennas for high-speed global satellite and space communications. Josh is a Westinghouse semi-finalist and published scientist. He previously worked in investment banking at Salomon Smith Barney and in capital markets at Merrill Lynch. In 2008 Josh co-founded and funded Kurion, a contrarian bet in the unlikely business of using advanced robotics and state-of-the-art engineering and chemistry to clean up nuclear waste. It was an unmet, inevitable need with no solution in sight. The company was among the first responders to the Fukushima Daiichi disaster. In February 2016, Veolia acquired Kurion for nearly $400 million—34 times Lux's total investment. Josh is a columnist with Forbes and Editor for the Forbes/Wolfe Emerging Tech Report. He has been invited to The White House and Capitol Hill to advise on nanotechnology and emerging technologies, and a lecturer at MIT, Harvard, Yale, Cornell, Columbia and NYU. He is a term member at The Council on Foreign Relations and Chairman of Coney Island Prep charter school, where he grew up in Brooklyn. He graduated from Cornell University with a B.S. in Economics and Finance.

Episode notesAn interesting podcast episode on the multiple delays that have kept Ethereum from its long-anticipated merge and kicked the difficulty bomb down the road.Since we recorded, more news broke about delaying the boom.How to Find Open Source Projects to Contributehttps://www.codetriage.com/https://www.coss.community/https://goodfirstissue.dev/A pretty cool write up on the creation of spring animations by a few Figma engineers.Looking to build your own image search engine? Check out APIs from Clarifai and Roboflow that make it easy to train your own ML model.A creative and interesting Codepen from a newly minted Figma engineer. And for those who enjoy the CSS art of yummy snacks, Cassidy's Codepen has a few treats.Yet another rumor about Apple's upcoming AR/VR headset. Will it ever arrive, and how would its demands for GPU-intensive work mesh with Apple's hardware ecosystem?

SHOW NOTES:SUMMARY: In this episode, Denise Murtha Bachmann and Matt Zaun talk about how companies can use AI to craft the right stories to tell their customers. DENISE MURTHA BACHMANN BIO: Denise is a Senior Account Executive at Clarifai.  She focuses on using AI to enhance companies' customer experience, effectiveness, and to reduce operational costs. For more info, check out Denise here | https://www.linkedin.com/in/brigittedenise/MATT ZAUN BIO: Matt is an award-winning speaker and storyteller who empowers organizations to attract more clients through the art of strategic storytelling. Matt's past engagements have catalyzed radical sales increases for over 300 organizations that range from financial institutions to the health and wellness industry. Matt shares his expertise in persuasion with executives, sales professionals, and entrepreneurs, who he coaches on the art of influence and how to leverage this for profits and impact. For more info, check out Matt Zaun here:https://youtu.be/pflQtzgP7X0https://www.linkedin.com/in/mattzaun/https://mattzaun.com/ 

Does someone have to understand computer coding to use AI? In this episode of the DATAcated on Air podcast, host Kate Strachnyi talks with Ian Kelk from Clarifai. Clarifai is creating a platform for people to utilize AI easily. Learn how Clarifai is working to simplify and improve the process of converting unstructured data to structured data. Listen until the end when Ian shares some funny examples of Clarifai's models. You will want to hear this episode if you are interested in... Ian's role at Clarifai [04:13] Unstructured data [09:09] AI and fake news detection [13:43] Humans vs. computers [16:29] Companies and computer vision [19:47] GPU shortages [24:37] Fun with model demos [30:62] Computer vision competition [47:57] Resources & People Mentioned Clarifai Geoffrey Hinton Automatic Fake News Detection: Are current models "fact-checking" or "gut-checking"? Clarifai | LinkedIn Clarifai | Twitter Clarifai | Facebook Connect with Ian Kelk On LinkedIn Connect with DATAcated http://www.datacated.com/ DATAcated on LinkedIn: https://www.linkedin.com/company/datacated1/ Kate on LinkedIn: https://www.linkedin.com/in/kate-strachnyi-data/ DATAcated on Twitter: https://twitter.com/datacated_ DATAcated on YouTube: https://www.youtube.com/datacated Subscribe to the DATACATED On Air podcast --- Support this podcast: https://anchor.fm/datacated/support

Patrick Eggen, Founding General Partner at Counterpart Ventures, talks about the different facets of corporate venture capital (CVC), where it has a real edge in the startup world, and why entrepreneurs should work with CVC investors. Patrick debunks some myths around CVC and shares his observations on how CVC and venture capital has evolved over the last decade.In this episode, you'll learn:[2:33] The advantages of being early in corporate venture capital[14:23] Myths about corporate venture capital[19:28] What founders need to know before meeting a corporate venture capital investorCause that Patrick is passionate about: Pediatric surgery research at UCSFAbout Guest SpeakerPatrick Eggen is the Founding General Partner at Counterpart Ventures. He has held key thought leadership around core investment themes ranging from hardware, software, adjacent verticals, and frontier tech. In his 13 years of direct venture investment experience, Patrick has been involved in 100+ transactions and 30+ exits. He actively sourced or served as a Board Member/Observer for Qualcomm Ventures investments in Clarifai, Cloudflare, Matterport, Noom, OpenSignal, Particle, Plivo, Sense360, Sparta Science, and Swift Nav.About Counterpart VenturesCounterpart Ventures is a San Francisco-based life cycle venture capital fund investing in B2B SaaS, mobility, and marketplace technologies that target nontrivial problems or fill missing gaps in large markets. Counterpart's portfolio includes: Zoom, Cruise, Matterport, ANNEX CLOUD, AptEdge, Cloudbeds, Glidian, Particle, and RPA Labs.Subscribe to our podcast and stay tuned for our next episode that will drop next Tuesday. Follow Us:  Twitter | Linkedin | Instagram | Facebook

This episode features Matt Murphy, Partner at Menlo Ventures. Learn what investors and board members look for in a CFO, hear how Matt built companies and his career,Matt is a partner at Menlo Ventures and invests multi-stage across AI-first SaaS (apps, DevOps, API platforms) and robotics. Since joining Menlo in 2015, Matt has led investments in Alloy.AI, Benchling, 6 River Systems (acquired by Shopify), Canvas, Clarifai, Carta, Envoy, Firehydrant, Harness, Heap Analytics, Hover, Netlify, Scout RFP (acquired by Workday), Upstart, Usermind (acquired by Qualtrics), Veriflow (acquired by VMware), Vivun, and Zylo. He also serves as a board member at Egnyte and a board observer at Datastax.

Zavain Dar invests at the intersection and union of cutting-edge biotech and software. He has led Lux's investments in Primer, a machine intelligence startup; Clarifai, which democratizes cutting edge deep neural networks; Auransa, which is developing novel medicines based on computational insight applied to genomic data; Recursion which uses automation and deep learning to develop drugs for rare diseases; Tempo Automation, which applies software and automation to electronics manufacturing; Rigetti Computing, which is fabricating some of the fastest quantum chips in the world; Braid, which is bringing AI to medical diagnostics; Visor, which aims to simplify tax preparation; Computable Labs, which is building a decentralized data marketplace; Cryptonumerics, a data control company acquired by Snowflake Computing; The Stacks Foundation, which is making Bitcoin programmable; Runway, which is putting machine learning tools into the hands of creators; LabGenius, a protein drug discovery company; Anagenex, a drug discovery company leveraging DNA encoded libraries; Hugging Face, an open-source company democratizing Natural Language Processing; Dyno Therapeutics, an AI-powered gene therapy company; and Thrive Earlier Detection, an early cancer detection company that Exact Sciences agreed to acquire for $2.15 billion in 2020.

Fashionably Late is proud to release our Female Founder Series. Each week in April, Fashionably Late will feature a different female founder. From the tech space to the wellness industry, our four business leaders are eager to share their journey, advice, and fun personal tidbits. This week we have Caroline McCaffery, Co-Founder & CEO Her story is one about following your passions, using them to drive your professional trajectory, and trusting yourself to transform your career at any point. Driven by her desire to constantly learn and solve problems, Caroline has met job, career, and industry shifts with an openness integral for her success of founding her own company. Her adaptability and excitement for online privacy, her company's sector, will empower you to take the risks necessary for finding professional fulfillment.    Starting her career when the .com bubble burst, Caroline has always been intrigued by and worked in the tech space. A lawyer by training, Caroline's first role as an attorney was at Gunderson Dettmer, a firm that works with startups in the tech and life sciences spaces. As a Corporate Securities Attorney, she aided startups with financing, often debt and equity, as well as mergers and acquisitions. Spending almost ten years with the firm, Caroline was able to get a lot of experience working with startups.    Excited and challenged by supporting startups, in 2011, Caroline transitioned into her first in-house role. Still eager to work in tech, she joined the marketing and advertising automation company, Sailthru. She notes that she started this position at a transition moment in the internet space, as big data emerged as the leading technology. As Sailthru processed online users' data, Caroline recognized a problem: how could users ensure how/if their digital information would be protected? Following her budding curiosity in data while still staying in her industry of expertise (tech), Caroline shifted her focus as an attorney to commercial and privacy.    These new interests in data security and privacy led her to seek another general counsel role at another tech start-up, Clarifai. She entered the AI facial recognition company in its early stages. She found her role morphing outside its job description, as she also supported the company's strategy and operations. By leveraging what she learned about startups while at a firm and as Sailthru's privacy-focused general counsel, as well as embracing her intuition and openness, Caroline became the VP of Business Affairs while retaining her General Counsel title.   Continuing to focus on privacy law while tackling unfamiliar strategy-based challenges as VP of Business Affairs gave her “a taste of the entrepreneurial side of [her]self.” As the “type of person who loves to constantly learn new things,” she recognized that new challenges and new opportunities to develop solutions fuel her drive.   In addition to expanding her hard skills while at Clarifai, Caroline also gained a much deeper understanding of AI and cybersecurity, contributing to her growing passion for technology and data privacy. From there, she developed a hunger to create tech to ameliorate issues affecting users' online protections. After meeting George Rosamond, her future co-founder and CTO, a conversation about anonymity online evolved into a problem they were determined to solve. The security questionnaires that companies send to potential vendors who process online information can 1000+ questions long, plaguing vendors. These are sent pre-sale and in some cases the vendor will spend hours to complete the questionnaire without even landing a sale!   Since she and George clearly identified the challenge they wanted to solve and through discussions, discovered potential software solutions, it seemed as if the natural next step would be to start their B2B SAAS company, ClearOPS. They even had large goals for ClearOPS working as a “wheel in the spokes” type of mode, in which their services can connect other businesses and ultimately improve privacy communications. George was ready to commit full-time to transition their idea into an executed product. But starting a business is never linear. For Caroline, first came her “professional identity crisis.”    Caroline wavered between staying at the job she loved, finding a new GC role, or following her dream to start ClearOPS. She asked, “Am I a lawyer? Am I capable of being a COO? .Or am I a founder?” As a lawyer, she is trained to circumvent risks. Pursuing a career marked by innumerous risks seemed like the choice to avoid. Even when she conducted extensive research to evaluate if there was a market for their security/privacy product- there was- she was still uncertain. Until one day at breakfast, she got the push needed to “take a leap of faith” to begin identifying as a founder.   Listen to Caroline's journey of founding and becoming ClearOPS CEO and you will realize that you do not have to be just one career label, as she constantly adapted to execute whatever work she wanted to get done. You will be motivated by how she and George completely pivoted their initial model after taking potential investors' “fair critical feedback.” Despite ClearOPS losing its biggest deal during the pandemic, as CEO, Caroline again adjusted to the circumstance, conducting business so that their company finished the year with a product on the market and multiple customers. ClearOPS' founding story is one of balancing the line between following your passions and adapting to meet the needs of your business, ever-evolving market, and customers' needs. Both Caroline and ClearOPS continue to meet goals, providing the team confidence that ClearOPS will be a central player in the growing privacy tech space.   A recurring theme in Caroline's narrative is that a passion for learning, then trying new things offers fulfillment and fuels success.   Topics covered in this episode:   Why it is in a startup's best interest to be proactive and hire a lawyer early Insight into evolutions within the internet space, including the emergence of big data and privacy  A lawyer's take on overcoming and managing risk The different lessons learned from working at a firm, as an in-house GC, and as a founder The importance of leaning on your support network and only taking “fair critical feedback” Why execution is more imperative than conjuring an idea    Links: https://www.clearops.io/

Cassidy is a Principal Developer Experience Engineer at Netlify. She's worked for several other places, including CodePen, Amazon, and Venmo, and she's had the honor of working with various non-profits, including cKeys and Hacker Fund as their Director of Outreach. She's active in the developer community, and one of Glamour Magazine's 35 Women Under 35 Changing the Tech Industry and LinkedIn's Top Professionals 35 & Under. As an avid speaker, Cassidy has participated in several events including the Grace Hopper Celebration for Women in Computing, TEDx, the United Nations, and dozens of other technical events. She wants to inspire generations of STEM students to be the best they can be, and her favorite quote is from Helen Keller: "One can never consent to creep when one feels an impulse to soar." She loves mechanical keyboards and karaoke. In this episode, listen to Cassidy talk about finding mentorship and how to stand out as an engineer. Cassidy also reflects on her favorite projects from her time at Venmo, Clarifai, CodePen and Netlify. Shownotes: Connect with Cassidy on her Twitter (https://twitter.com/cassidoo) or GitHub (https://github.com/cassidoo). Subscribe to Cassidy's weekly web dev newsletter (https://cassidoo.co/newsletter/) and check out her course on Building Reusable React (https://scrimba.com/learn/reusablereact).

Abhishek Mathur highlights how critical it is to approach the field of AI with a holistic lens - in the training data, the applications, and the team behind it. He also discusses the increasing need for AI ethicists, his transition from consulting into product, and the varying skillsets and roles needed in the AI industry that expand beyond technical development. Subscribe for episodes every other Thursday!— Guest: Abhishek Mathur — Abhishek is a product management leader, an artificial intelligence practitioner, and an educator. He has led product management and engineering teams at Clarifai, IBM, and Kasisto, to build a variety of artificial intelligence applications within the space of computer vision, natural language processing, and recommendation systems. Abhishek enjoys having deep conversations about the future of technology, and helping aspiring product managers enter and accelerate their careers.TwitterLinkedIn— Links — Yes! Machine Learning Is Fun!Andrew Ng’s intro to AI on Coursera: AI For EveryoneNext, consider taking his Machine Learning course as well!Big Tech AI Blogs: Facebook, Microsoft, Google, AppleOpen AI’s GPT-3, the most powerful language model to date, can be used to design websites, write creative fiction, and more.— A.I. For Anyone, a non-profit dedicated to helping you learn about AI.  —Find us on Instagram, Twitter, Facebook, LinkedIn and YouTube at @aiforanyonecheck us out at aiforanyone.org/podcastsend us your feedback and guest recos here!email your friends at podcast@aiforanyone.orgBrought to you by Haroon Choudery (@haroonchoudery), Mac McMahon, Serena Chao (@coriils), Nandana Yadla, Jacob Ludwig, and the rest of the AI4A team

What should you know about the state of surveillance in the world today? What can we do as consumers to stop unintentionally contributing to surveillance? The Facial Recognition industry had a reckoning after the murder of George Floyd - are things getting better? To answer these questions we welcome Liz O'Sullivan to the show. Liz O'Sullivan is the Surveillance Technology Oversight Project's technology director. She is also the co-founder and vice president of commercial operations at Arthur AI, an AI explainability and bias monitoring startup. Liz has been featured in articles on ethical AI in the NY Times, The Intercept, and The Register, and has written about AI for the ACLU and The Campaign to Stop Killer Robots. She has spent 10 years in tech, mainly in the AI space, most recently as the head of image annotations for the computer vision startup, Clarifai. Full show notes for this episode can be found at Radicalai.org.  If you enjoy this episode please make sure to subscribe, submit a rating and review, and connect with us on twitter at twitter.com/radicalaipod      

Today we’re taking a break from our CVPR coverage to bring you this interview with Deb Raji, a Technology Fellow at the AI Now Institute at New York University.  Over the past week or two, there have been quite a few major news stories in the AI community, including the self-imposed moratorium on facial recognition technology from Amazon, IBM and Microsoft.There was also the release of PULSE, a controversial computer vision model that ultimately sparked a Twitter firestorm involving Yann Lecun and AI ethics researchers, including friend of the show, Timnit Gebru. The controversy echoed into the broader AI community, eventually leading to the former’s departure from Twitter.  In our conversation with Deb, we dig into these stories in depth, discussing the origins of Deb’s work on the Gender Shades project, how subsequent work put a spotlight on the potential harms of facial recognition technology, and who holds responsibility for dealing with underlying bias issues in datasets. The complete show notes for this episode can be found at twimlai.com/talk/388.

Matt Zeiler, Founder and CEO at Clarifai, shares his amazing personal story that led to founding of Clarifai and his views on the state of image recognition today. We discuss about Clarifai's AI platform capabilities and applications of image recognition in business. We end with Matt's take on the future of computer vision in business

How can the environment that you're in and the types of people you're exposed to change your entire outlook on life? Listen to our final episode through to the end because near minute 20, Susan drops something unexpected and the conversation takes a turn. Join us as we dive into Susan's experience of moving from Sacramento and going to work at Google where she (literally) was pushed into a sink or swim situation. Susan Chy is the New York City based Recruiting Manager for Revolut, a British fintech company. Prior to moving to NYC and the startup world, Susan worked on recruiting for companies like Clarifai, PAX Labs (the makers of JUUL), Amazon and Google. -- This episode is sponsored by Underdog.io, a marketplace connecting job seekers with technology companies. Want more heartfelt content? Follow us on Instagram and LinkedIn. If this podcast inspires you, please rate, review and share with your network. Together, we can put more heart into the recruitment process for everyone. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/hiringfromtheheart/message Support this podcast: https://anchor.fm/hiringfromtheheart/support

Today's guest is Matt Zeiler, Founder, and CEO of Clarifai. Clarifai is one of the first startups to apply modern deep learning for image recognition. Their tools are currently used by clients like Staples, OpenTable, and the US Department of Defense (DoD). In this episode, Matt sheds light on the company's founding story and how an internship at Google was the catalyst for the creation of Clarifai. He also talks about what it's like competing against industry giants like Facebook and Google. Clarifai's algorithm and their ability to collaborate rather than compete with their clients truly sets them apart. Matt also sheds light on the benefits of the network effect for both the customers and the company. Matt talks about some of the interesting use cases of their technology, like Trivago, which uses image recognition to organize hotel photos or how the DoD uses it in natural disaster recovery. Matt believes that AI is a great service to the government in helping citizens in many ways, and Clarifai is incredibly proud to be a partner. Tune in to learn more about AI image recognition and be inspired by Matt. “At Clarifai, we don't compete with our customers. We want to be seen as that partner that is going to take your data, learn from it to solve your business problems together.” “I really think that AI is going to be better than humans in so many different ways, and it's already better than humans in a lot of ways for very specific use cases.” Key Points From This Episode: Learn more about Matt's background, his Ph.D., and what ultimately led him to start Clarifai. Seven years on: Clarifai's products, their customers and how they use the products. Some of the other applications of AI that Clarifai is potentially interested in getting into. How Clarifai aims to gain a competitive advantage. Why the API model works so well in the AI image recognition space. The different mix of products Clarifai customers use and why they choose them. Learn about the benefits that customers get from sharing their information on Clarifai. Why there is not really a limit to how large Clarifai's model can grow. Where Matt sees Clarifai's potential labeling feature taking the company in the future. Matt's experience of working with the government and why he is proud to work with them. How AI could be used in natural disaster recovery efforts. The potential of video in the space, the neural network structures, and various use cases. Matt's insights into the AI competition between the US and China.

Today’s guest is Matt Zeiler, Founder, and CEO of Clarifai. Clarifai is one of the first startups to apply modern deep learning for image recognition. Their tools are currently used by clients like Staples, OpenTable, and the US Department of Defense (DoD). In this episode, Matt sheds light on the company’s founding story and how an internship at Google was the catalyst for the creation of Clarifai. He also talks about what it’s like competing against industry giants like Facebook and Google. Clarifai’s algorithm and their ability to collaborate rather than compete with their clients truly sets them apart. Matt also sheds light on the benefits of the network effect for both the customers and the company. Matt talks about some of the interesting use cases of their technology, like Trivago, which uses image recognition to organize hotel photos or how the DoD uses it in natural disaster recovery. Matt believes that AI is a great service to the government in helping citizens in many ways, and Clarifai is incredibly proud to be a partner. Tune in to learn more about AI image recognition and be inspired by Matt.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill.

Phil’s guest on this episode of the IT Career Energizer podcast is Cassidy Williams. She is a software engineer at CodePen and the director of outreach at cKeys.  Previously, she has worked for Amazon, L4 Digital, Clarifai and Venmo. She also runs a weekly newsletter and loves teaching and helping people become better coders.  In this episode, Phil and Cassidy Williams discuss the benefits of getting involved with the wider community and teaching them tech skills. They talk about the need to constantly evaluate the work you are doing to make sure that it is still right for you. Phil and Cassidy also review how the frontend is changing and what the websites of the future will look like.   KEY TAKEAWAYS: (4.18) TOP CAREER TIP Know what you don’t want just as much as what you do. If you do not want to work in a certain kind of environment or use a specific tech knowing that is the case is essential. You have to avoid that kind of work even if it looks like it will take you closer to your dream job. Putting yourself in an uncomfortable place to reach your ultimate goal rarely works out. Usually, you just end up feeling miserable. At which point, it is all too easy to give up on your dream.   (6.08) WORST CAREER MOMENT A few years ago, Cassidy was offered a well-paid job with a good title at Amazon. Despite the fact that it was going to be practically impossible to maintain the level of life-work balance she had been enjoying at her previous firm, she took the job. For Cassidy, this turned out to be a huge mistake. She no longer had the time to work on side projects and got very little job satisfaction out of her new role. It was a tough way to learn what really mattered to her.   (9.04) CAREER HIGHLIGHT In the podcast, Cassidy shares four great highlights from her career. Including her work at Clarifai which gave her the chance to build a programme from the ground up and share it with the world.   (13.28) THE FUTURE OF CAREERS IN I.T Cassidy is really excited by the direction that frontend development is going in. React, Angular and Vue have really mixed things up and the possibilities are now endless. These more advanced front ends will make websites a lot faster, more functional and accessible.   (15.42) THE REVEAL What first attracted you to a career in I.T.? – Creating her first website is what got Cassidy hooked on IT. What’s the best career advice you received? – Ask yourself, what’s the worst that could possibly happen? Cassidy finds that thinking this way stops her from worrying too much and unnecessarily holding herself back. What’s the worst career advice you received? – Sign up for absolutely everything. It will make you better at time management. Following that advice will lead to burn out and leave you working on things you don’t really care about. What would you do if you started your career now? – Cassidy would start out by working for a large company. Then move onto working with smaller firms and start-ups. In the podcast, she explains how this can benefit your career. What are your current career objectives? – Cassidy is figuring out how she can earn enough relatively passive income, so she can spend more time working on side projects that interest her. What’s your number one non-technical skill? – Communication, both speaking and writing. In the podcast, Cassidy explains how she went about developing these skills. How do you keep your own career energized? – Working on interesting side projects is what keeps Cassidy’s career energized. It is the main way she learns about new tech. What do you do away from technology? – Cassidy and her husband are musicians, so they both spend a lot of time playing music. She also loves making funny videos and coming up with new jokes.   (22.12) FINAL CAREER TIP Periodically, sit down and have a meeting with yourself about where your career is going. Every quarter or so, review your goals, objectives and what you are working on. Make sure that you are happy with what you are doing and where you are going. At this stage of the podcast, she shares the questions you should be asking to ensure that you stay on track and enjoying the work that you are doing.   BEST MOMENTS (4.34) – Cassidy - “Know what you don’t want just as much as what you do want.” (13.06) – Cassidy - “Technical workers should take full advantage of the freedom being able to work from anywhere offers them.” (18.06) – Cassidy - “Start your career working for a large firm, later you can switch to smaller firms.” (20.01) – Cassidy - “Learn to effectively communicate what you are thinking and don’t be afraid to ask questions.” (22.23) – Cassidy - “Periodically, take time out to honestly evaluate your career and ensure the work you are doing will keep you happy.”     ABOUT THE HOST – PHIL BURGESS Phil Burgess is an independent IT consultant who has spent the last 20 years helping organisations to design, develop and implement software solutions.  Phil has always had an interest in helping others to develop and advance their careers.  And in 2017 Phil started the I.T. Career Energizer podcast to try to help as many people as possible to learn from the career advice and experiences of those that have been, and still are, on that same career journey.   CONTACT THE HOST – PHIL BURGESS Phil can be contacted through the following Social Media platforms: Twitter: https://twitter.com/philtechcareer LinkedIn: https://uk.linkedin.com/in/philburgess Facebook: https://facebook.com/philtechcareer Instagram: https://instagram.com/philtechcareer Website: https://itcareerenergizer.com/contact Phil is also reachable by email at phil@itcareerenergizer.com and via the podcast’s website, https://itcareerenergizer.com Join the I.T. Career Energizer Community on Facebook - https://www.facebook.com/groups/ITCareerEnergizer   ABOUT THE GUEST – Cassidy Williams Cassidy Williams is a software engineer at CodePen and the director of outreach at cKeys.  Previously she has worked for Amazon, L4 Digital, Clarifai and Venmo. She also runs a weekly newsletter and loves teaching and helping people become better coders.     CONTACT THE GUEST – Cassidy Williams Cassidy Williams can be contacted through the following Social Media platforms: Twitter: https://twitter.com/cassidoo LinkedIn: https://www.linkedin.com/in/cassidoo/ Website: https://cassidoo.co/  

This week we spoke to Deborah, who split her PEY between 12 months at Clarifai in New York City and 4 months at the MIT Media Lab! Notes 1:20 - getting into engineering, previous work experience and first jobs at JR Deep and with Project Include, becoming interesting in working in tech 3:45 - developing skills through attending lots of hackathons, attending TechCrunch Disrupt! 6:20 - learning about Clarifai in NYC and computer vision in school, deciding on doing PEY 10:00 - Embarking on a campaign to find a job at a startups, getting a job at Clarifai 13:00 - Work experience at Clarifai, startup work culture 18:10 - Transitioning to a role that felt more like a full-time position 20:05 - Living in Manhattan, moving to Brooklyn 22:20 - Neighborhood culture, comparing Toronto, Ottawa, and NYC, having space for personal growth 27:42 - Summer research at MIT Media Lab, "anti-disciplinary research" 30:45 - Finding out about the researcher through a TED Talk, research in algorithmic/data bias 36:17 - Other things going on at the lab, prosthetics, "do-ocracy" vs a meritocracy 39:58 - Constraints of industry vs. research, justifying research, corporate sponsored research 43:20 - Life outside of work, meeting cool hip musical friends in Cambridge 45:24 - Differences between MIT and UofT, "intersession", alumni relations 52:02 - Coming back and appreciating Toronto in a new way, changes to plans for 4th year 56:00 - Mentorship, machine learning twitter Links Twitter Campaigning for jobs, another one TED Talk on algorithmic bias Music by Shawn Lee

In this week's DataTalk, we chat with Matt Zeiler, Founder and CEO of Clarifai, about ways businesses are using computer vision. Matt Zeiler, Founder and CEO of Clarifai, is a machine learning Ph.D. and thought leader pioneering the field of applied artificial intelligence (AI). Matt’s groundbreaking research in computer vision alongside renowned machine learning experts Geoff Hinton and Yann LeCun has propelled the image recognition industry from theory to real-world application.

In this week's #DataTalk, we chat with Dr. Ryan Compton about computer vision. Dr. Ryan Compton is the Head of Applied Machine Learning at Clarifai and previously served on the research staff at Howard Hughes Laboratories. In 2012, Ryan completed a PhD in Applied Mathematics — which involved studying sparsity promoting optimization in quantum mechanical signal processing.

Last summer, a sign appeared on the door to a stuffy, windowless room at the office of Manhattan artificial intelligence startup Clarifai. “Chamber of secrets,” it read, according to three people who saw it. The notice was a joking reference to how the small team working inside was not permitted to discuss its work with others at Clarifai.

Keybase is a platform for managing public key infrastructure. Keybase’s products simplify the complicated process of associating your identity with a public key. Keybase is the subject of the first half of today’s show. Michael Maxim, an engineer from Keybase gives an overview for how the technology works and what kinds of applications Keybase unlocks. The post Keybase Architecture / Clarifai Infrastructure Meetup Talks appeared first on Software Engineering Daily.

The podcast you’re about to hear is the second of a series of shows recorded at the NYU Future Labs AI Summit last week in New York City.In this episode, you’ll hear from Bite.ai, a startup founded by Vinay Anantharaman and Michal Wolski, founders who met working at Clarifai, another NYU Future Labs alumni, whose CEO Matt Zeiler I interviewed on TWiML Talk #22(Link on show notes page). Bite is using convolutional neural networks and other machine learning to help computers understand and reason about food. Their product is the app Bitesnap, which provides users with detailed nutritional information about the food they’re about to eat using just a photo and a serving size. We dive into the details of their app and service, the machine learning models and pipeline that enable it, and how they plan to compete with other apps targeting dieters, and more! The notes for this show can be found at twimlai.com/talk/65 For series information, visit twimlai.com/ainexuslab2.

Clarifai CEO Matt Zeiler talks about how artificial intelligence and neural networks are getting smarter, learning how to automatically recognize images more quickly and accurately. AI companies should build their own neural networks in-house, but everyone else should borrow the expertise of outside firms like Clarifai, Zeiler says. He explains the potential of "visual search" for shopping, helping customers find and buy things that they can't quite describe in words. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Today we bring you our final interview from backstage at the NYU FutureLabs AI Summit. Our guest this week is Matt Zeiler. Matt graduated from the University of Toronto where he worked with deep learning researcher Geoffrey Hinton and went on to earn his PhD in machine learning at NYU, home of Yann Lecun. In 2013 Matt’s founded Clarifai, a startup whose cloud-based visual recognition system gives developers a way to integrate visual identification into their own products, and whose initial image classification algorithm achieved top 5 results in that year’s ImageNet competition. I caught up with Matt after his talk “From Research to the Real World”. Our conversation focused on the birth and growth of Clarifai, as well as the underlying deep neural network architectures that enable it. If you’ve been listening to the show for a while, you’ve heard me ask several guests how they go about evolving the architectures of their deep neural networks to enhance performance. Well, in this podcast Matt gives the most satisfying answer I’ve received to date by far. Check it out. I think you’ll enjoy it. The show notes can be found at twimlai.com/talk/22.

Artificial intelligence can do remarkable things, like recognize faces on social networks, instantly translate speech from one language to another, and identify commands barked into a smartphone. But it also can do stupid things, like label an African-American couple "gorillas." The artificial intelligence underpinning Google Photos did just that last year. The platform uses deep neural networks to identify images in your photo collection.