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9 episodes with slms
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2 episodes with slms
2 episodes with slms
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2 episodes with slms
2 episodes with slms
Her early inspiration while growing up in Goa with limited exposure to career options. Her Father's intellectual influence despite personal hardships and shift in focus to technology.Personal tragedy sparked a resolve to become financially independent and learn deeply.Inspirational quote that shaped her mindset: “Even if your dreams haven't come true, be grateful that so haven't your nightmares.”Her first role at a startup with Hands-on work with networking protocols (LDAP, VPN, DNS). Learning using only RFCs and O'Reilly books—no StackOverflow! Importance of building deep expertise for long-term success.Experiences with Troubleshooting and System Thinking; Transitioned from reactive fixes to logical, structured problem-solving. Her depth of understanding helped in debugging and system optimization.Career move to Yahoo where she led Service Engineering for mobile and ads across global data centers got early exposure to big data and machine learning through ad recommendation systems and built "performance and scale muscle" through working at massive scale.Challenges of Scale and Performance Then vs. Now: Problems remain the same, but data volumes and complexity have exploded. How modern tools (like AI/ML) can help identify relevance and anomalies in large data sets.Design with Scale in Mind - Importance of flipping the design approach: think scale-first, not POC-first. Encourage starting with a big-picture view, even when building a small prototype. Highlights multiple scaling dimensions—data, compute, network, security.Getting Into ML and Data Science with early spark from MOOCs, TensorFlow experiments, and statistics; Transition into data science role at Infoblox, a cybersecurity firm with focus areas on DNS security, anomaly detection, threat intelligence.Building real-world ML model applications like supervised models for threat detection and storage forecasting; developing graph models to analyze DNS traffic patterns for anomalies and key challenges of managing and processing massive volumes of security data.Data stack and what it takes to build data lakes that support ML with emphasis on understanding the end-to-end AI pipelineShifts from “under the hood” ML to front-and-center GenAI & Barriers: Data readiness, ROI, explainability, regulatory compliance.Explainability in AI and importance of interpreting model decisions, especially in regulated industries.How Explainability Works -Trade-offs between interpretable models (e.g., decision trees) and complex ones (e.g., deep learning); Techniques for local and global model understanding.Aruna's Book on Interpretability and Explainability in AI Using Python (by Aruna C).The world of GenAI & Transformers - Explainability in LLMs and GenAI: From attention weights to neuron activation.Challenges of scale: billions of parameters make models harder to interpret. Exciting research areas: Concept tracing, gradient analysis, neuron behavior.GenAI Agents in Action - Transition from task-specific GenAI to multi-step agents. Agents as orchestrators of business workflows using tools + reasoning.Real-world impact of agents and AI for everyday lifeAruna Chakkirala is a seasoned leader with expertise in AI, Data and Cloud. She is an AI Solutions Architect at Microsoft where she was instrumental in the early adoption of Generative AI. In prior roles as a Data Scientist she has built models in cybersecurity and holds a patent in community detection for DNS querying. Through her two-decade career, she has developed expertise in scale, security, and strategy at various organizations such as Infoblox, Yahoo, Nokia, EFI, and Verisign. Aruna has led highly successful teams and thrives on working with cutting-edge technologies. She is a frequent technical and keynote speaker, panelist, author and an active blogger. She contributes to community open groups and serves as a guest faculty member at premier academic institutes. Her book titled "Interpretability and Explainability in AI using Python" covers the taxonomy and techniques for model explanations in AI including the latest research in LLMs. She believes that the success of real-world AI applications increasingly depends on well- defined architectures across all encompassing domains. Her current interests include Generative AI, applications of LLMs and SLMs, Causality, Mechanistic Interpretability, and Explainability tools.Her recently published book linkInterpretability and Explainability in AI Using Python: Decrypt AI Decision-Making Using Interpretability and Explainability with Python to Build Reliable Machine Learning Systems https://amzn.in/d/00dSOwAOutside of work, she is an avid reader and enjoys creative writing. A passionate advocate for diversity and inclusion, she is actively involved in GHCI, LeanIn communities.
Neste episódio do Product Guru's, Paulo Chiodi conversa com Anderson Amaral, um dos maiores especialistas em Agentes de IA e LLMs no Brasil, segundo a própria comunidade de tecnologia no LinkedIn. Fundador da Scoras Digital e Scoras Academy, Anderson compartilha sua trajetória, explica a diferença entre LLM, SLM e agentes autônomos, além de mostrar na prática como funciona um sistema multiagente de IA.A conversa aborda temas técnicos e estratégicos com leveza e profundidade: desde o impacto de ferramentas como Devin e Manus AI no futuro do desenvolvimento de software, até os riscos éticos e técnicos do uso de IA em larga escala. Anderson ainda dá dicas valiosas para quem quer começar a aprender IA na prática, destacando oportunidades de carreira, ferramentas como LangGraph e os desafios da área em 2025. Um episódio essencial para PMs, devs e criadores de produtos digitais.//// Onde encontrar o convidada: Anderson Amaral | Co-Founder @ Scorashttps://www.linkedin.com/in/andersonlamaral/// Recado Importante: O futuro dos produtos digitais já começou e a Inteligência Artificial é parte do time.A PM3 acaba de lançar a Formação em Gestão de Produtos de IA: um curso pensado para Product Managers que querem criar, delegar e inovar com mais inteligência. Muito além dos prompts: você vai aprender a liderar produtos baseados em IA, dominar temas como Machine Learning, Deep Learning e IA Generativa, e aplicar novas formas de discovery, experimentação e validação.Prepare-se para o mercado que mais cresce no mundo e torne-se o PM que lidera a transformação.Acesse o link e saiba mais: https://go.pm3.com.br/ProductGurus-AI-Specialist/// Outros parceiros:Codando sem Codar - A maior comunidade de AI (Vibe) Coding do Brasil: https://codandosemcodar.com.br/?utm_campaign=pg_podcastCurling - Do treinamento à criação de soluções com IA, estamos em cada etapa. https://www.usecurling.com//// Nesse episódio abordamos:A combinação de múltiplos LLMs para resolver tarefas de forma coordenada. Scoras Academy já formou quase 500 alunos em menos de 6 meses. A diferença entre LLM e agente é que o agente age no mundo com base em instruções fixas. Modelos chineses como o DeepSeek são mais eficientes e baratos por design. O LandGraph é uma ferramenta poderosa para criar sistemas multiagente personalizados. Pequenos modelos (SLMs) resolvem 80% dos problemas empresariais de IA. O maior desafio atual não é técnico, mas ético e de segurança no uso da IA. Profissionais introspectivos e sem habilidade de comunicação tendem a ser substituídos por IA. Agentes de IA têm potencial para gerar golpes e deepfakes — mais perigosos que NFTs. Comece com casos reais simples e depois evolua para soluções como LangGraph e DuckDB./// Capítulos00:00 Introdução e apresentação do convidado01:41 Origem da Scoras e a criação das empresas04:30 Crescimento da Scoras Academy e carência de talentos no Brasil07:59 Cupom e convite para estudar na Scoras Academy10:28 Diferença entre LLM e agentes autônomos16:09 Como funciona o treino de modelos de IA19:29 Por que modelos chineses são mais baratos?23:08 DeepSeek e eficiência computacional29:08 Demonstração prática: como funciona um sistema multiagente39:10 Diferença entre LLM e SLM (Small Language Model)42:08 Desafios técnicos e éticos dos agentes de IA48:12 Agentes de IA viraram o novo "NFT"?54:28 O futuro do desenvolvimento com IA e ferramentas como Devin01:00:06 Conselhos práticos para quem quer aprender IA01:07:28 Encerramento e convite final/// Onde encontrar a Product Guru's:WhatsApp: https://whatsapp.com/channel/0029Va7uwHS5fM5U0LIatu3XX (antigo Twitter): https://twitter.com/product_gurusLinkedIn: https://www.linkedin.com/company/product-guru-s/Instagram: https://www.instagram.com/product.gurus/
“Before starting a new AI project, it is really worthwhile defining the business priority first,” asserts Joanna Hodgson, the UK and Ireland regional leader at Red Hat.“What specific problem are you trying to solve with AI? Do we need a general purpose AI application or would a more focused model be better? How will we manage security, compliance and governance of that model? This process can help to reveal where AI adoption makes sense and where it doesn't," she added. In this episode of the Tech Transformed podcast, host Shubhangi Dua, podcast producer at EM360Tech speaks with Hodgson, a seasoned business and technical leader with over 25 years of experience at IBM and Red Hat. They talk about the challenges of scaling AI projects, the importance of open source in compliance with GDPR, and the geopolitical aspects of AI innovation. They also discuss the role of small language models (SLMs) in enterprise applications and the collaboration between IBM and Red Hat in advancing AI technology. Joanna emphasises the need for a strategic approach to AI and the importance of data quality for sustainable business practices. While large language models (LLMs) dominate headlines, SLMs offer a cost-effective and efficient alternative for specific tasks.The podcast answers key questions, like ‘how do businesses balance ethical considerations, moral obligations, and even patriotism with the drive for AI advancement?' Hodgson shares her perspective on how open source can facilitate this balance, ensuring AI works for everyone, not just those with the deepest pockets.Hodgson also provides her vision on the future of AI. It comprises interconnected small AI models, agentic AI, and a world where AI frees up teams to create personal connections and exceptional customer experiences.TakeawaysCuriosity is a strength in technology.AI is becoming embedded in existing applications.Regulatory compliance is crucial for AI systems.Open source can enhance trust and transparency.Small language models are efficient for specific tasks.AI should free teams to create personal connections.A strategic AI platform is essential for businesses.Data quality is key for sustainable business success.Collaboration in open source accelerates innovation.AI can be used for both good and bad outcomes.Chapters00:00 Introduction to the Tech Transform Podcast01:35 Pivotal Moments in Joanna's Career05:12 Challenges in Scaling AI Projects09:15 Open Source and GDPR Compliance13:11 Regulatory Compliance and Data Security17:30 Geopolitical Aspects of AI Innovation22:31 Collaboration Between IBM and Red Hat23:58 Understanding Small Language Models29:54 Future Trends in AI and SustainabilityAbout Red HatRed Hat is a leading provider of enterprise open source solutions, using a community-powered approach to deliver high-performing Linux, hybrid cloud, edge, and Kubernetes technologies. The company is known for Enterprise Linux.They offer a wide range of hybrid cloud platforms and open source...
Google, Microsoft and Meta have all pledged to reach at least net-zero carbon emissions by 2030. Amazon set their net-zero deadline for 2040. To understand how these four tech companies could possibly meet their climate goals amid an artificial intelligence renaissance, Short Wave co-host Emily Kwong discusses the green AI movement. Speaking with scientists, CEOs and tech insiders, she explores three possible pathways: nuclear energy, small language models (SLMs) and back-to-the-future ways of keeping data centers cool. Listen to Part 1 of Short Wave's reporting on the environmental cost of AI here. Have a question about AI and the environment? Email us at shortwave@npr.org — we'd love to hear from you!Listen to every episode of Short Wave sponsor-free and support our work at NPR by signing up for Short Wave+ at plus.npr.org/shortwave.Learn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy
Thrill of the Hill is back for season 6! Armed with a new team, new ideas and a range of new speakers, Alex takes on the hot topics impacting the farmed upland environment.Scotland has a vibrant and dynamic farming industry, merging traditional practices with new innovations, yet barriers and challenges to entering and exiting the industry remain. Established in 2019 in response to industry concerns over the lack of new entrants across the sectors, the Scottish Land Matching Service (SLMS) offers a range of free services, providing advice and guidance, tools and signposting and a comprehensive database of individuals seeking opportunities in farming. In this episode Ian Davidson OBE gives us an overview of SLMS, what it does, who it works with and who it is looking for, highlighting some of the opportunities and successes through the initiative – across farming and crofting. Want to get in touch with Ian? He can be contacted at the Scottish Land Matching Service via email enquiries at slms@nfus.org.uk Note: This episode was recorded in March 2025Related FAS ResourcesNew Entrants resources for farmers from Farm Advisory ServiceSpecialist Advice | Helping farmers in Scotland | Farm Advisory ServiceRelated External ResourcesScottish Land Matching Service | Opportunities in Scottish Farming
Thrill of the Hill is back for season 6! Armed with a new team, new ideas and a range of new speakers, Alex takes on the hot topics impacting the farmed upland environment.Scotland has a vibrant and dynamic farming industry, merging traditional practices with new innovations, yet barriers and challenges to entering and exiting the industry remain. Established in 2019 in response to industry concerns over the lack of new entrants across the sectors, the Scottish Land Matching Service (SLMS) offers a range of free services, providing advice and guidance, tools and signposting and a comprehensive database of individuals seeking opportunities in farming. In this episode Ian Davidson OBE gives us an overview of SLMS, what it does, who it works with and who it is looking for, highlighting some of the opportunities and successes through the initiative – across farming and crofting. Want to get in touch with Ian? He can be contacted at the Scottish Land Matching Service via email enquiries at slms@nfus.org.uk Note: This episode was recorded in March 2025Related FAS ResourcesNew Entrants resources for farmers from Farm Advisory ServiceSpecialist Advice | Helping farmers in Scotland | Farm Advisory ServiceRelated External ResourcesScottish Land Matching Service | Opportunities in Scottish Farming
For this week's paper read, we actually dive into our own research.We wanted to create a replicable, evolving dataset that can keep pace with model training so that you always know you're testing with data your model has never seen before. We also saw the prohibitively high cost of running LLM evals at scale, and have used our data to fine-tune a series of SLMs that perform just as well as their base LLM counterparts, but at 1/10 the cost. So, over the past few weeks, the Arize team generated the largest public dataset of hallucinations, as well as a series of fine-tuned evaluation models.We talk about what we built, the process we took, and the bottom line results.
What happens when the hype around generative AI starts to mature, and businesses begin asking harder questions about performance, risk, and long-term value? In today's episode, I'm joined by Mike Mason, Chief AI Officer at Thoughtworks, to explore how 2025 is shaping up across the enterprise AI landscape—from the rise of intelligent agents to the growing traction of small, nimble models that prioritize security and specificity. Mike brings a deep, practical perspective on the evolution of AI inside complex organizations. He unpacks how AI agents are moving well beyond basic chatbots and starting to integrate into actual business workflows—performing as teammates that can reason, adapt, and even collaborate with other agents. We dig into examples like Klarna's workforce transformation and examine how this shift could play out across customer service, internal ops, and software development. We also look at what's fueling the boom in open source AI and how companies are navigating the balance between transparency, IP protection, and regulatory readiness. Mike shares why some financial services firms are turning to in-house fine-tuned models for greater control, and how open-weight and fully open-source models are starting to gain real ground. Another key theme is the momentum behind small language models. Mike explains why bigger isn't always better—especially when it comes to data privacy, edge deployment, and resource efficiency. He outlines where SLMs can outperform their larger counterparts and what that means for companies optimizing for security and speed rather than brute force compute. We also discuss Thoughtworks' forthcoming global survey, which reveals a growing divide in generative AI adoption. While mature players are building in bias detection and robust compliance frameworks, newer entrants are leaning toward fast operational gains and interpretability. This gap is shaping how GenAI projects are prioritized across industries and geographies, and Mike offers his take on how leaders can navigate both speed and safety. So, what role will explainability, regulation, and open ecosystems play in shaping the AI tools of tomorrow—and what should business and tech leaders be planning for now? Let's find out in this wide-ranging conversation with Thoughtworks.
Software Engineering Radio - The Podcast for Professional Software Developers
Sunil Mallya, co-founder and CTO of Flip AI, discusses small language models with host Brijesh Ammanath. They begin by considering the technical distinctions between SLMs and large language models. LLMs excel in generating complex outputs across various natural language processing tasks, leveraging extensive training datasets on with massive GPU clusters. However, this capability comes with high computational costs and concerns about efficiency, particularly in applications that are specific to a given enterprise. To address this, many enterprises are turning to SLMs, fine-tuned on domain-specific datasets. The lower computational requirements and memory usage make SLMs suitable for real-time applications. By focusing on specific domains, SLMs can achieve greater accuracy and relevance aligned with specialized terminologies. The selection of SLMs depends on specific application requirements. Additional influencing factors include the availability of training data, implementation complexity, and adaptability to changing information, allowing organizations to align their choices with operational needs and constraints. This episode is sponsored by Codegate.
Learn how many enterprises have monetized their LLMs! Hazem El-Hammamy from Microsoft shares how you can leverage Azure AI Foundry to monetize your LLMs, SLMs, and other agentic IP. We discuss:Model Catalog: Access to first-party and third-party models like GPT-4, Meta's Llama, and more.Models as a Service: Simplified deployment and monetization without needing your own GPUs.Workshops & Events: Upcoming sessions on real-time intelligence, data warehousing, and AI insights with Microsoft Fabric.Success Stories: Featuring partners like NTT DATA with their Tsuzumi model.Stay tuned for more updates and join us in our upcoming workshops! #MicrosoftAzure #AI #LLM #TechInnovationOur weekly meetup on Azure AI topics is at https://aka.ms/meetup . Connect with us on LinkedIn at Hazem El-Hammamyand James Caton .Chapters• 00:00 Introduction to Generative AI Monetization• 00:58 Introduction to Monetizing LLMs• 04:35 Understanding Models as a Service• 09:48 Live Demo of Model Catalog• 12:34 Exploring Azure Marketplace• 17:48 Model Onboarding Process• 27:16 Fine-Tuning Models as a Service• 30:49 Q&A and Audience Interaction
Was ist beim KI-Einsatz im Unternehmenskontext zu beachten? Unser Podcast-Gast Rolf Löwisch, Head of AI bei IBM in der DACH-Region, klärt über die Herausforderungen und Chancen von KI-Einführungen auf. Im Gespräch beleuchtet er die Unterschiede zwischen LLMs und SLMs. Zudem erzählt er, wie es Unternehmen schaffen eigene Daten in KI-Modelle einfließen zu lassen, ohne die Daten dabei preiszugeben?
On this episode of The Founder's Sandbox, Brenda speaks with Chasity Lourde Wright. Chasity is inventor and founder of Infiltron Software Suite LLC. Infiltron operates in the cybersecurity space; a Service disabled-Veteran owned and women-owned small business. Infiltron offers quantum-resistant cybersecurity solutions for decentralized digital identity, digital assets, and AI governance, utilizing proprietary post-secure encryption. Its patented technology integrates AI, blockchain, and quantum-resistant encryption to provide advanced cyber resilience, compliance enforcement, and real-time threat mitigation across multiple industries, including aerospace & defense, fintech, smart cities, and EVs. Chasity, as inventor, speaks about her team and how creativity in the work place is necessary for enhancing innovation on really tough problems like Cybersecurity. As the CEO of Infiltron, Chasity Lourde Wright is also a former USAF Aerospace Engineer, Intel Officer, and Cybersecurity Instructor with extensive experience in cybersecurity, AI governance, and national security. She was part of the team that developed reconfiguration capabilities for the USAF C-130 and contributed to the creation of the CMMC framework since its inception in 2019. Additionally, she has engaged in high-level cybersecurity and AI governance initiatives, including industry collaborations, government advisory roles, and proprietary innovations in quantum-resistant encryption, AI security, and blockchain-based compliance solutions. Her expertise extends beyond participating in NIST challenges, encompassing leading-edge cybersecurity development, policy influence, and defense sector innovations. You can find out more about Chasity and Infiltron at: https://www.linkedin.com/in/infiltronsoftwaresuite/ https://infiltron.net/ Transcript: 00:04 Hi, I'm pleased to announce something very special to me, a new subscription-based service through Next Act Advisors that allows members exclusive access to personal industry insights and bespoke 00:32 corporate governance knowledge. This comes in the form of blogs, personal book recommendations, and early access to the founder's sandbox podcast episodes before they released to the public. If you want more white glove information on building your startup with information like what was in today's episode, sign up with the link in the show notes to enjoy being a special member of Next Act Advisors. 01:01 As a thank you to Founders Sandbox listeners, you can use code SANDBOX25 at checkout to enjoy 25% off your membership costs. Thank you. 01:19 Welcome back to the Founder's Sandbox. I am Brenda McCabe, your host of this monthly podcast in which I bring entrepreneurs, founders, corporate directors, and professional service providers who, like me, want to effectuate change in the world by building resilient, scalable, and purpose-driven companies. I like to recreate a fun sandbox environment with my guests. And we will touch on not only their purpose, 01:47 and what has driven them to create their own businesses. But also we're going to touch upon topics such as resilience, purpose-driven, and scalable sustainable growth. Today, I am absolutely delighted to have as my guest Chasity Wright. Welcome, Chasity. Hey. Thank you for having me. 02:13 Super excited to talk about how Infiltron has evolved and the lessons learned and how we're preparing to relaunch in 2025. Excellent. And it's perfect timing because I've known you for a couple of years now. Yeah. Right. So Chasity is CEO and founder of Infiltron Software Suite, a company that's headquartered out of Atlanta. 02:40 She is oftentimes in Los Angeles because she's working largely in the defense market and cyber security. So I wanted to have you on my podcast because you have gone further in building your business. So you and I met, I want to say back in 2022, you came out of the Women Founders Network cohort. 03:08 kind of very early stage. One of the events that I was a host of was the Thai So Cal Women's Fund. And you weren't yet ready for investing, but we struck up, I would say a friendship and I admire many things about you as, and we'll get into it in the podcast here, but you touch. 03:35 quite a few or check of quite a few boxes for my podcast. You says, so you are a woman owned veteran and women owned business. You are a veteran of the Air Force. You're in deep tech and you're by park and queer. And so there's many many boxes that you check and it was difficult to kind of hone in on what I really wanted to bring into the podcast today, but we're going to we're going to start from here. 04:05 I always like to ask my guests to start with kind of their origin story. I, when I first met you, right, in private conversations, got to hear your origin story and why you do what you do, what your firsthand experience while on missions, right, that really informed your aha moments to create infiltrant. 04:33 as a cybersecurity company. So tell us a bit about your origin story, Chasity. So, I mean, my origin story has, if you can imagine all of these different paths kind of streamlining into one path. So one of those paths would be a little black girl born in Georgia, still seeing dirt roads and... 05:01 being able to go to the country and work on a farm and, you know, just still having that connection to the past, you know, and not necessarily the past in a bad way. So athletic, played ball in college, went to Clark Atlanta University, you know, the HBCUs are a big hurrah right now, but they've always been one. 05:29 I grew up with one in my backyard, Fort Valley State, which is in Fort Valley, Georgia. So, you know, roughed it with the boys, played in the backyard with the boys, always been a boys girl, cousins, neighbor. We're all still close. We all still play sports when we meet. So it's like an adult play date, so to speak. But also, you know, 05:58 raised religiously, you know, I'm in Southern Baptist Church, two parent household, maybe lower middle class, but middle school was very transformative for me because they decided to mix in everybody. So it was my first time, you know, being in a more diverse population in school. 06:25 And, you know, music is a big thing for me as well. I DJ, I make music. That's the creative part of me. And I found a lot of people in deep tech to do something with music. So, yeah, so, you know, that's my like early years background. And then coming through, I decided to go into the Air Force. I actually took off between my junior and senior year at Clark Atlanta. 06:52 Um, there I was majoring in global leadership and management. Okay. And went in and I was in for eight years. I was an aerospace engineer, uh, got deployed several times, uh, to different places, and that kind of brings us to why Infiltron exists and, um, on one of those deployments, I was a part of a network takedown. 07:21 And it was, whoo. I mean, I don't mean to quote the pitch deck story, but it is what it is. I wrote it because that's the way it felt. It was catastrophic. So just imagine the city of Los Angeles losing power out of nowhere. The rail stops working, Sinai has no power, so all of the medical equipment is no longer working. 07:49 The internet's completely gone and not rebooting like it normally would. Your energy grid is down. That is what I experienced in one of those deployments. And I was a part of Iraqi freedom and Afghanistan. I was a part of both of those wars. And when we came, you know, we got everything back. Thank God we were smart enough to ship. 08:19 brand new equipment. Okay, you know, so you know, we weren't able to get there. Yeah. I mean, I mean, that's part of our job. We're engineers. And when you're in the middle of nowhere, there's no calling HP. There's no calling Cisco. Like you got to know how to do what needs to be done. There was there was a lot of makeshifting. I can be I came out of Air Force, I could be a mechanical engineer to 08:45 because we had to figure out how to make components on the fly. It was just so many things. Innovation, right? Like you had to be innovative. You had to be adapt quickly while keeping the mission as a focus. So just imagine something that catastrophic and something similar has happened. I feel like Colonial Pipeline was something that is known now in the US for sure. 09:15 that had similar elements of what we experienced in being deployed. Yeah, and that was two years back. And SolarWinds is another one. I generally refer to those because people generally gasp, even non-technical people, because they know how damaging it was. So we can reuse. Normally, when the equipment goes down, 09:44 Unplug, right? Plug back in. Reboot. Yeah, reboot. But that was not happening. And what we found out in the debrief was that quantum was used. So quantum simplistically is about frequencies in this context. It's about frequencies. And frequencies matter in so many aspects of life, from spirituality all the way through tech like what Infotron has. So... 10:14 What they did was they basically zeroed out the frequencies of our satellite communications. And I believe that they created some frequencies that damaged other equipment. So these are things that again we found out in the debrief. And I wasn't really able to talk to that probably when we met because I wasn't sure if it was unclassified yet. 10:42 But as soon as Biden started talking about quantum initiative, which was back in 2022, when we were in, I was like, everything's hitting it the right time because we were literally in Techstars LA space. And Biden pushed the quantum initiative. And I'm like, see, told you, because a lot of people, a lot of people doubted what I was saying because of the year that I said it had happened. And as. 11:09 we started to grow out our team. There are other veterans on our team from different branches. And of course we war story swap all the time. And those other two people work for like NSA and they did kind of the same thing, telecommunications. And I'm telling the pitch desk story and they're sitting there like, yep, yep. That happened to us too. And I'm like, when? 11:38 And they're saying different years. So at that point, we understood it. It happened more than once. So that's why Infiltronic. So what's Infiltronic? So let's bring it back to, Yeah. So you leave, you leave service after eight years after also experiencing that. I still feel like I'm a part of it because I do consult them still. Right. So it'd be great. So. 12:08 And once in the Air Force forever? Always. Well, I really would have been in Space Force. Yes. Yeah. Well, you heard that here on the Founder Sandbox. The next, yes. So for my listeners, again, you check a lot of boxes. Deep tech, women in STEM. What is it exactly that? 12:37 your suite of services. All right. So Info-Trans software, right, has two patents now. And on your landing page, it says, our patented solutions, solutions utilize adaptive artificial intelligence, advanced quantum encryption and blockchain technology to deliver real-time cybersecurity for a wide array of applications. Later on, we'll get into smart cities, but 13:06 including the internet of things, smart devices, legacy systems, hybrid data, signals and devices. All pretty, pretty understandable, but what is it that Infiltrion software is able to do that others are not? So we're able to create a easier way for businesses to migrate their devices. 13:36 and their software, so their applications that they use, maybe they've developed them themselves, we provide a way for them to easily migrate those entities over into a more quantum-proofed infrastructure. So we created what we've trademarked as quantum encapsulation. So just imagine something being encapsulated. And basically we've created, 14:05 a brand new method of leveraging quantum, the AI, we leverage it for the pro-activeness. So in lieu of just waiting for threats to happen to our clients, we go look for the threat. So we want to go be where the bad guys are and find out and bring that information back and update the solution in real time to provide protection for all of our clients in real time. 14:33 That's how we leverage the AI. The blockchain is kind of leveraged to kind of make sure that people, things like devices, aren't on networks that shouldn't be. So it's kind of, I mean, we use it for what blockchain was pretty much basically developed for, and that's a ledger. So keeping up with the transactions of what's happening. 15:03 in a client's infrastructure. Fantastic. So it's largely a B2B business, yours, right? We do. We have B2B, but we've been approached several times here recently by consumers. Because now, because of the biometric protection aspect of our solution using the quantum encapsulation, we can protect, say, 15:32 Halle Berry from deep fake, being deep faked, or, you know, protecting her likeness from being used without her knowledge in movies, CGI'd into movies. So it's kind of getting a little bit more consumerish as we iterate, right? Yeah, and we were briefly speaking before the podcast recording, Chasity and I, and... 15:59 I've known her for years. She's a very private person, would not allow photographs. So I told my producer, I'm certain Whitney Chastity's not going to be sending us a picture, but you said yes, that you might, because you do have biometric, artificial intelligence, safeguards that can actually discover deep fakes, right? Yes, yes. Yep, if it didn't come from us, if it wasn't checked back from us, 16:29 It wasn't approved by the person. So it's kind of pretty much that simple. Amazing. Well, later on in the show notes, we will have how to contact you at Enfield Tron. So you are in the startup ecosystem. Again, you travel a lot. You're between Washington DC, Atlanta, Los Angeles, and actually the Bay Area. Yeah, the Bay Area. Right. So. 16:58 Revenue can be elusive, right? How? Especially in tech, and especially in these really large markets that I call deep tech. Deep tech and leading edge, bleeding edge, right? People don't know what they're actually buying, right? Or what they don't even, they probably don't even know that they have a need, right? What's been your strategy at Infiltron to keep the revenue flowing while maintaining also a pretty playful, innovative culture? 17:27 You talked about your team and so talk, that's kind of two questions. So how have you kept revenue coming, right? While not going out for dilutive funding yet, but tell us a little bit about how, what's your business model? So the business model in itself is set up for B2B and we also have a licensing element there. So if they, for instance, 17:56 a Fortune 500 company who has a cyber team, right? They have an internal cyber team. If they want to license out the patents that we have and kind of customize it or create or build off of those, use it as a baseline for what they need for their systems, we offer that as well. But let me just put it out there. But back to your question, how do we keep it fun? So the team... 18:25 The original team members, should I say. So we met about seven years ago at a place called the Gathering Spot in Atlanta. So the Gathering Spot is a community and they just opened one in LA and I do go to the one in LA too when I'm there. But it's a community of people, creatives from creative people to deep tech people like myself and everything in between. 18:55 We went to a black tech event at the gathering spot and found ourselves not being able to get into the actual room. So we ended up, because they have a bar and everything at the gathering spot. It's a social club too. It has a club aspect to it too, but you can network there, have meetings there, meet all types of people. I mean known people, I mean it's a great 19:25 great concept, shout out to Ryan. But we found ourselves at the bar, and we're looking at each other. We knew each other because we had been introduced by the Hellbrella person, Tracy. Yes, yes. Because they had done some things for her with a previous startup that she had, development-wise. So we're all sitting at the bar, and we're looking at each other like, but we're the real tech people. 19:55 We do it. It's like we don't really take people. Um, we can't even get in there. We like, we know the organizers and personally and everything. So let's start a company. Well, what we did was we launched, um, what we launched kit labs. And it was literally right down the street from the 20:23 and connect to the community. So we had, it's not far from the AUC and the AUC is where Morris Brown, Morehouse, Spelman and Clark Atlanta are. Got it. So a lot of times you would come in there and find some of the founders, cause this was founded by myself and like six or seven other black tech founders. The ones that were outside. Drinking like, you know. 20:53 That's where we had that conversation. You know, the conversation started at the bar, being outside of that first Black Tech meetup, so to speak, with Joey Womack, who is a part of Goody Nation, who we did get a 50K grant from back in 2020 through Google for Startups. Let me just say this so much. We were so interconnected. I mean, Atlanta is Wakanda. Don't let anybody tell you anything different. 21:21 It's definitely Wakanda. But literally, not even a mile away from the Gathering Spot, we opened up Kit Labs. It's a smart lab where we can tinker with stuff. We're engineers. We're tech people. We need something. We need a makerspace. We don't necessarily need a space that is compared. The Gathering Spot was a little bit more buttoned up. 21:46 And then what we needed, we needed to be able to throw things and make things. We had everything from like 3d printers to, um, VR, AR headsets. I mean, you, anything in tech. Innovative fun. It was in, is in that lab. Um, but that's where around today. So we dissolved it. So it's been dissolved. What one of, one of the founders, he unfortunately transitioned. Um, 22:15 So, you know, and he was kind of like the pillar of it. And it kept going for a while, but it was just a lot of people like myself, it was two female founders, Dr. Nashley Cephas, who herself is from Jackson, Mississippi. I'm shouting out everybody, right? She's from Jackson, Mississippi, and she bought 10 acres in downtown Jackson, Mississippi and started a nonprofit called Bean Pad. And he basically took the concept of what we were doing at Kit Labs and brought it to our hometown. So. 22:44 Um, and it's so funny. She actually founded it on my birthday. So I was like, okay, I can dig that. Um, uh, but, but no, but we're still connected. Everybody still works with each other. You know, if I have to come in and do some things around cyber for a contract or, you know, commercial or whatever client that they have, I do like we, we all kind of still work together on each other's things. So that has allowed you to bring in some revenues, right? 23:14 through its service context. Yeah. Oh, for sure. For sure. Consultant wise, cause they're like, I think people may look at Infotron and think that there's not a human touch piece there, but if you're dealing with me, there's always gonna be a human touch point there because we have to consult the client. We can't assume, you know, we cannot assume. 23:41 what you need, we have to actually have a conversation with our clients throughout the process, even after we possibly have set up the platform for you, trained your people on it, there still needs to be an element of communication, human communication, right? But the team, we've been working together for about seven years. Yes. 24:10 Infiltron has been around for five, going on six years now. So, you know, I mean, respect, mutual respect, we're still kids at heart. I mean, we grew up wanting to be engineers. So, you really can't take the light of innovation out of an engineer unless they're just at the point of not wanting to do it anymore. So we're always, what I've found is most people in any engineering discipline are very, 24:39 curious and forward thinking. So we, and we kind of, we're kind of like a community. We are community and not kind of like, but we are community of folks that contribute to each other's, you know, projects. Yeah. Mm-hmm. And not just, not just business-wise, but personally, like we, I mean, we've been around each other for almost a decade, so. 25:04 there's been kids born and like I just said, one of our founders transitioned, like we've been through some things together that have brought us closer together. And you can, I believe when you have a team like that, and we're all diverse, you know, we have a team like that that cultivates innovation, for sure. You know, I've had a few guests to my podcast and I also write about this, 25:35 Creativity is only possible or it's greatly possible when you create a fun environment and make games out of things and have, right? And set up teams. So I think a shout out to you and what you've set up at Infiltron and in its earlier rendering at Kit Labs, just creating an environment that allows for what ifs, right? Is key. There are a lot of what ifs in cyber. 26:04 I bet you there. So I have a boatload of questions here. One is, before we get into your fundraising path, again, I mentioned earlier you have two patents that have been issued. What is post-quantum encryption technology in layman language? Post. 26:32 Quantum encryption technology. So there is definitely confusion out there that has been addressed. And because there is a difference between post secure quantum and encryption. There's a difference. So. Excellent. 27:02 Post quantum encryption, it is designed to protect data from quantum computers. So. And that's done through the encapsulation? For us, that is how we provide the protection, the encryption. That is the quantum encapsulation is a method of encryption with Involtron. So the current encryption. So you have things like RSA. 27:32 elliptical curve, which elliptical curve is more widely used and kind of being marketed as quantum encryption. It is, it is, it's on the list of quantum protections, right, or quantum methods of encryption protection. So companies like Okta use ECC a lot. But what's happening is that quantum computers are being built now. Yes. Like right now, there's no... Yeah, the cost is going down. 28:02 Yeah, there's no waiting five years from now. Like I urge anyone under the sound of my voice to prepare now for quantum computer attacks. The same thing that I describe happening to us when we were deployed, it's gonna happen. And again, I alluded to feeling like 28:33 situations like Colonial Pipeline and SolarWinds were, I feel like they were tests because there were so many different elements of what we saw in the deployment that happened in those two cases. Yeah, because I'm sitting there and think it's like 2020, 2021, 2019 actually, it started. I think this didn't know, but. 28:59 And it's still going like 20, SolarWinds was still going, the last time I checked SolarWinds was still unraveling. Like it's still, still going. But back to the question. So for us, quantum encapsulation for us is breakthrough. So NIST has had these challenges, right? Where they put out bidding for companies, 29:27 researchers, because a lot of people that are in the quantum space, whether it's physics, mechanics, are generally found in academia. They're not at Infiltron. They're not at QED. They're just not there, right? It's very far in between, and we generally have to lure them. Or we have to do something like partner with them on... 29:53 grants, like the STTR grants. Like that's the only way, generally the only way that we can probably connect with the academia or pierce them and have them work with us. And they usually through that take all the funding, but it's, you're still. Exposed, right? You're exposed, but you're also getting the expertise that you possibly need and can't rightly find in the freelancing world. Yeah. So it generally works out in the long run. 30:23 Um, but so our encapsulation is a, is a breakthrough method because I look at it like this, NIST is holding these challenges and nothing against NIST. We're connected. I contribute to NIST and everything, but they are holding these challenges. And basically they're telling the hackers what people are going to the framework. 30:49 what people are gonna have to adhere to when they create their quantum algorithms to protect their devices and data. You know, you're giving away the secret ingredients. So like, even if they don't know specifically your algorithm, they know what you've based it off of. And that gives it like a tiny thread can unravel a whole t-shirt, right? So I look at it like that. So... 31:15 And even before, you know, we were already developing things before NIST put out these challenges. We are in alignment. We can adhere and do it here to the framework that they're putting out because, you know, you have the DOD space who definitely follows their framework, especially when it comes to the risk management framework. So they're going to follow NIST regardless. They're going to follow their framework, whatever they put out about cybersecurity protection. 31:44 The DOD space and all of its agencies are gonna follow that. However, being in the cybersecurity space every day, seeing what is happening and knowing that you've given some clues, some contextual clues to the malicious hackers about what you're using as a baseline to build your algorithms will, guess what? What we have is not that. Like we are... 32:12 One of the things that differentiates us right now, because I'm sure as quantum cybersecurity continues to grow legs, so to speak, people are gonna start using the more, less susceptible to hacks by quantum computers method. So you have things like multivariate hash code. So these are some of the 32:40 quantum properties that you can use that are not generally hackable by a quantum computer. They won't be hackable by a quantum computer. So we leveraged some of that. It was like, if I'm built, I looked at it like this, I've been in cyber, I've been in tech for almost 20 years. I know I don't look it. I get it all the time. You don't have to say it. I've been in tech for almost 20 years. I've been, and when I was in the air force, we call it InfoSec. It's the same thing. And that dates me. 33:08 If I say, if you hear somebody say InfoSec, trust me, they've been in cybersecurity for at least 20 plus years. So, but it's cybersecurity, that's what it is. And I've seen the changes and I've paid my dues too. Like I didn't, when I got out of the Air Force, I was just, side note, like I cut grass and loved it. I would go back and do it if I can make these results. So then like, it's very, it's very fulfilling. Don't let anybody fool you. Like I love, but I like being outside, but. 33:38 Um, my first tech job though, I literally went through the phone book. Cause this is like still, you know, internet was not quite what it is now, of course, but it was like still growing. And I went through the yellow pages and went through the aerospace companies and called all of them and was like, Hey, let's just get out of the air force, look for a job. I don't care if it's an intern or co-op and L3 L3 before they merged with Harris. Uh, 34:08 they created me a co-op. And, but again, still in touch with, cause you know, L3 is a huge government contracting company, right? And in the satellite communication space, cause they're in line with my background. And so I've seen it all. I've seen the changes of InfoSec into cybersecurity. And now we're entering a new frontier with quantum cybersecurity. So I've been here, 34:37 maybe at the latter part of the info set, but definitely through the cybersecurity and here for and to forge some guidelines and pathways in the quantum cybersecurity space with Inflotron. So when you know Inflotron was founded in 2019, I was like, okay, if I'm gonna start 35:03 something new in cyber and we hadn't even gotten to the quantum piece yet. They hadn't even gotten to me yet. Like it started like I was getting downloads. Yeah. Because I'm, I always, I'm a reader. I wake up looking at cyber news and just staying in the know because I need to know what's going on so I can protect my clients, whether that was me in a government contracting position or me as a consultant in my businesses. So. 35:33 I need to know what's going on. And if I'm going to build something new, why am I going to build it with compromised parts? Right. That's a great way to describe it. Yeah. Forget the tech. It didn't make logical sense. If I'm going to build something new, a SaaS product that's going to integrate and be flexible and adaptable and proactive. 36:01 Why would I use RSA encryption when I know what's coming? Got it. That will be one of the snippets that I share in my YouTube channel as well as the podcast. That is excellent. Why build something with compromised parts? Frontier technology, quantum cybersecurity is what Epfiltron is about. 36:30 Next generation. Talk to me a little bit more for us, less tech savvy listeners about the use of Infiltron in a SelleGov's program for smart cities. That kind of brings it more home and more tangible. How is technology used for smart cities? So first, SelleGov through leading cities. Yes. 36:59 It connects companies like ours with municipalities to tackle urban challenges. So for us, it's infrastructure, security, and sustainability. So we were a finalist in leading cities global competition back in 2021. And we've worked through them. You know, we've been able to work with city leaders to secure IOT systems and critical infrastructure. 37:28 And quick shout out to Michael Lake. Okay. He's the founder of Leading Cities, amazing guy. Another keep in touch, answer the email quickly person. He's based in Boston, but he's built a very supportive ecosystem. So shout out to Michael Lake. But as a part of this program, 37:56 We're offering smart cities our enhanced quantum vulnerability assessment. And this is to help the smart city leaders identify areas that need better quantum protections now. We've just had a session on November the 11th, Veterans Day. And the second one is coming up December the 5th. So you. 38:24 If you're a smart city leader or see so small, medium, large enterprise, no matter what market you in, you're in, definitely tap in. You can register for it on the leading city's website or on our website at Infotron.net. Yeah, that's on December 9, 2024 at 1pm. Is that Eastern? December 5th. December 5th? No, it's the 9th, because I have it here. And that's my cousin's birthday. So yeah, it's December 9th. 38:53 Did you get to influence those dates? Yeah. So let's jump into your startup. You've taken in very little dilutive funding. How much money have you raised to date? And how have you, what is the next phase, right? In terms of outreach for fundraising. So we've raised 120K and that was through Techstars, LA Space. 39:23 Still counting. I do not take a salary. I could take one, but I'm just, it's the long game for me. And I still consult. Don't let these people tell you not to quit your job and be an entrepreneur. Don't let people do that. Especially if you have a family. Don't let these people, don't let these people try to guilt you or shame you because you still have a job while you're building your startup. Don't let, don't do it. 39:53 Because I do have a company that I started called Right Tech Solutions and we still, that's why I said I still feel like I'm in the Air Force because I still consult them. So I can, you know, the revenue that we do and we've hit 500K in revenue. So you know, I could easily take a salary, right? But I just, it's the long game for me. It's the global expansion. 40:22 um, you know, more IP and patents, uh, protections, right? Because we do have global count clients. And, um, one of the things that I wanted to make sure of before we even took on the clients was that we had legal backing there. So IP trademarks, um, at least patent, at least the application is pending, but you know, like I want to, I want to, I want it to at least have that. And we have great attorneys. Um, shout out to Malika Tyson. 40:52 and Matthew and Dorian who have, they took over because I had a, I had an attorney, IP attorney that would, had her own boutique firm and then she had to go back, you know, she just couldn't do the entrepreneurship, it's not for everybody, but we still stay in contact as well. But she introduced me to McAndrews, they're based out of Chicago. 41:20 And they are the legal team for Impletron. I always tell them that when we're on calls, like you are the legal team. Like, yeah, anything that I need from them legal, legal wise, they do it. I literally just sent a partnership NDA over to Malekka this morning and she just sent it back to me. So like, that's not IP and trademark, right? But they do, they do it. And I always tell them how much I appreciate them because... 41:49 IP and trademarks are not free and they're not inexpensive. So, and then imagine, you know, we have one pending now in Japan. We just got one in Canada. So yeah, like it's expensive, you know, it's expensive. So a lot of the funding that we get now is going to be allocated to pay them, you know, even though they work with us. But it's going to be paying them. 42:18 doing some iterations, we have a partnership where there's some hardware that's gonna be involved. We're definitely tapping into the hardware. So we'll be forging our way there because people like things they can touch. SaaS isn't necessarily something that you can touch, although put it into a platform makes it a little bit more tangible for people, visual at least. So in the- 42:48 Yeah, I mean, hardware has always been a part of the vision. FBGAs, we have another colleague of mine, he has developed a cryptocurrency mining machine, and it leverages quantum. So it's mining at exponential speeds, right? Because generally what quantum does is speeds things up. It speeds exactly, in simplified terms. 43:18 Definitely still going after Sivers traditional government contracts globally. We participated in Fintech down in the Bahamas last October. Cause we are in the Fintech space and there's a lot of similarities between Fintech and Space Tech. Because when you're talking about fault zeros and being able to detect anomalies. 43:46 both of those markets need that and they need it quick. So we've been able to, yeah, like we've been able to leverage some of the things that we're learning in both of those for each other. So we've been able to participate in some conferences. We actually getting ready to go to Barbados in January for Fintech Islands, I'll be speaking about 44:14 the kind of the intersection of the quantum age and what's coming in respect to the fintech space, cryptocurrency, web three, traditional finance and AI, because we do leverage AI. And we've been in the AI space, Impletron has been in the AI space from the beginning. One of our advisors is an AI evangelist at AWS. I did say her name earlier on this podcast, but. 44:42 She's amazing. She's a Georgia Tech grad. We do have a few Georgia Tech people on the team, but she's amazing. And I'm able to tap her. I've been able to tap her because she was one of the Kit founders. So I've been able to tap her about AI and machine learning very early on. So all of the LLMs and the SLMs that everybody's kind of talking about, we've been doing. 45:11 Like even as small as we are, we've been. 45:16 Yeah, so, Chasity, how can my listeners contact or get information about Infotron? So, yeah, of course the website. So, infiltron.net. You can follow us on all of our socials at Infotron Software Suite. It might be, I think on Twitter is Infotron app. We wanted to keep it short. 45:41 And then, or you can email us at mfultronapp at gmail.com. And I know people are gonna be like, why you use Gmail? That's another filter. And that's an email that everybody on the team can look at and not be bombarded with, cause spam and it's just, everybody has their own email address, but. So you probably, it's a test environment for all of you. 46:09 beautiful quantum encryption that you're working on. Yes. And that's it all. One better way to start. Yeah, Gmail, right? Google knows a lot more about us than we'd like them to. Oh, Google knows everything. That's tough. Even when you turn location off. Oh, Instagram. I just posted something about Instagram. So Instagram's new. They just updated their policy maybe a month ago, maybe. 46:38 Okay. Whether you want to or not, they now have access to your photos, your GPS location, everything even if you say no, even if you turn it off, they still contract. 47:00 Just putting it out there guys. Yeah. So if you do platform. So there's cause to the platform. Right? Yes. Thank you. All right. We're coming down to the section of the podcast where I like to ask each of my guests what the following three words mean to you. Because this is what I do with my consulting business. 47:24 In addition to my podcast, I work with founders that are really building resilient, purpose-driven and scalable businesses. What's resilience mean to you, Chasity? Man, that's a word that I use. Uh, I mean, I'm, I mean, you gotta think about it. I'm black trying to raise money. It's hard for black people to raise money on top of that. I've been, you know, um, I've come face to face with people that didn't believe that I wrote my own patents. Like. 47:53 you know, as if black people didn't invent a lot of things, like that we still use today. Like, come on. I mean, it's just the truth. Resilience. Resilience for me is bending, but never breaking. Bending, but never breaking. Yeah. It's about, you know, adapting to challenges. I just mentioned some and facing them. Like you can't, you can't, and I'm about to sound 48:23 run from the pain, you gotta run towards it. So you can come out stronger on the other side. And it's not necessarily about survival, it's transformation. That's transformation. It's transformation. And that transformation is preparing you for what's next. And you'll be standing taller than you were before. Amazing, thank you. Purpose-driven, what's a purpose-driven? 48:53 Enterprises or? Yeah. I'm a visionary. So like, there's a lot of founders that I've met. If I have the opportunity to get close to them or kind of hear them speak about what they're building to include myself, because I do talk to myself about the things that I'm building. I counsel myself. I'm sure my ancestors are around me. 49:23 Purpose is, it should be intentional. I think that it's kind of interchangeable for me. But in the context of the question that you asked on purpose driven enterprise, so it's the heartbeat in what we build here at Infotron. I can definitely say that. It's creating meaningful solutions that solve real problems. And in solving those real problems, 49:52 you're still staying true to the mission. I still bring the aspect of the military into Infiltron. We are mission focused. We have fun. We do all the fun things, right? Because again, that cultivates innovation too. And it keeps it spicy. You need to let things be spicy because in a regular deglar cybersecurity job, you're probably bored. Like. 50:19 I mean, let's just be real. Like you're probably bored. You're probably looking at Excel spreadsheets and creating a report by hand from that. Like it's boring. Like, but you know, it's also making moves that matter. And it's solving problems that for me leave a legacy and just never losing sight of why we started in the first place. 50:48 So never lives in sight. Excellent. What about scalable? So how does- That's one of those BC's favorite words. That's right. Because that's what they want to see. How will you scale? That's right. I mean, I'm an investor too guys. Don't get it twisted. Like, I think that was a question that I did ask with one of the investors I had. Like, how are you going to get over that challenge? Like, before I give you this money. 51:18 Scalable. So growth, like we can think about growth in so many different ways, like growth, personal growth, because if you embark on the entrepreneur trick, you are going to be, and need to be open to growth. To me, entrepreneurship is a spiritual journey. Beautiful. 51:45 about the Southern Baptist roots, but I'm not spiritual. I'm a yoga, meditating, put my feet in the sand, grass grounding person nowadays, but still bringing that element of praying. And it's all the same to me. They just changed the name of God, right? Just that's my perspective, but growth isn't just about getting. 52:14 bigger. It's about getting better. And me speaking about the personal aspect, that is what growth is. It might not feel good, you know, while it's happening. But, you know, once you get through it and you can get in a reflective mindset and look back with what you just came through and be grateful, like find gratitude in it, you know. 52:43 That's how I look at growth. It's expanding mindfully and staying grounded in your values and making sure that every step that you take going forward strengthens the foundation that you've already built. And it's... 53:11 Like I said, it's moving with intention. And while you're moving with intention, you're also preserving the quality and the vision that define you. Which goes back to purpose-driven. Yes, thank you. Last question, Chasity. Did you have fun in the sandbox? Oh yeah, I mean, it's you. You know, we already have a great rapport. 53:38 I'll say this, one of my favorite memories of you is when you brought Ty to the table to kind of see if they were, could invest in Infiltron and it was too early. But we had to sign an NDA, it was some type of contract, but it was during Mercury retrograde. You said it before I said it, I was like, I wonder if she's onto this type. 54:05 Cause I wasn't going to sign it. I was going to try to delay it as much as possible, but you're like, no, let's wait, let's wait. So after Mercer, that's your great. Well, I was like, oh, these are this. She's my people. And I was like, and I think I responded like, let's wait five days. So it is no, it's like clear. So, um, that's a little fighter for me with you. Oh, I love it. I love it. Generally hear that in business. No, no. 54:32 And the Founder Sandbox again is a pretty eclectic podcast, bringing in deep tech founders like Chasity Wright that are on the frontier, bringing in what the future, will, it's the future's here. It's here. That's right. So to my listeners, if you like this episode with Chasity Wright, CEO and founder of Infiltron, sign up for the monthly release of 55:01 this podcast where founders, business owners, corporate directors, and professional service providers share their own experiences on building with strong governance, a resilient, scalable, and purpose-driven company to make profits for good. So signing off for this month, thank you, Chasity. Thank you, Brenda, so much. I hope to see you soon.
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today, we're joined by Chris Lott, senior director of engineering at Qualcomm AI Research to discuss accelerating large language model inference. We explore the challenges presented by the LLM encoding and decoding (aka generation) and how these interact with various hardware constraints such as FLOPS, memory footprint and memory bandwidth to limit key inference metrics such as time-to-first-token, tokens per second, and tokens per joule. We then dig into a variety of techniques that can be used to accelerate inference such as KV compression, quantization, pruning, speculative decoding, and leveraging small language models (SLMs). We also discuss future directions for enabling on-device agentic experiences such as parallel generation and software tools like Qualcomm AI Orchestrator. The complete show notes for this episode can be found at https://twimlai.com/go/717.
Proprietary LLM builders need to experience a valuation haircut as open source LLMs take share from proprietary LLMs. Proprietary LLM builders (OpenAI, Anthropic, Google, Microsoft, Amazon), have enjoyed lofty valuations over the past several years. Given the rise of open source competitors - which are on par with proprietary models from a performance standpoint and can be operated at a fraction of the cost - the proprietary model builders should suffer a valuation haircut. I believe that open source LLM builders such as DeepSeek and META will win the day and that 80% of LLMs and SLMs in production 5 years from now will be open source language models. https://open.substack.com/pub/tek2day/p/valuation-haircut-is-due-for-proprietary?r=1rp1p&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false
By now you probably know the term “large language model.” They’re the systems that underlie artificial intelligence chatbots like ChatGPT. They’re called “large” because typically the more data you feed into them — like all the text on the internet — the better those models perform. But in recent months, there’s been chatter about the prospect that ever bigger models might not deliver transformative performance gains. Enter small language models. MIT Technology Review recently listed the systems as a breakthrough technology to watch in 2025. Marketplace’s Meghan McCarty Carino spoke to MIT Tech Review Executive Editor Niall Firth about why SLMs made the list.
By now you probably know the term “large language model.” They’re the systems that underlie artificial intelligence chatbots like ChatGPT. They’re called “large” because typically the more data you feed into them — like all the text on the internet — the better those models perform. But in recent months, there’s been chatter about the prospect that ever bigger models might not deliver transformative performance gains. Enter small language models. MIT Technology Review recently listed the systems as a breakthrough technology to watch in 2025. Marketplace’s Meghan McCarty Carino spoke to MIT Tech Review Executive Editor Niall Firth about why SLMs made the list.
By now you probably know the term “large language model.” They’re the systems that underlie artificial intelligence chatbots like ChatGPT. They’re called “large” because typically the more data you feed into them — like all the text on the internet — the better those models perform. But in recent months, there’s been chatter about the prospect that ever bigger models might not deliver transformative performance gains. Enter small language models. MIT Technology Review recently listed the systems as a breakthrough technology to watch in 2025. Marketplace’s Meghan McCarty Carino spoke to MIT Tech Review Executive Editor Niall Firth about why SLMs made the list.
Cale and Sujit discuss their current projects in Azure as 2024 comes to a close. They also cover a ton of AKS updates. Semantic Kernel makes it easier for developers to build Azure Open AI applications that can also include SLMs like Phi-4. Azure has many options to use File Shares and Volumes, and we walk through the process of figuring out which one is right for your needs. Media file: https://azpodcast.blob.core.windows.net/episodes/Episode511.mp3 YouTube: https://youtu.be/dLfCJ6btKng Resources: Semantic Kernel - https://github.com/microsoft/semantic-kernel Journey with SK on OpenAI and AzureOpenAI Ollama (running SLM local) - https://github.com/ollama/ollama Ollamazure (running SLM that looks like Azure OpenAI) - https://github.com/sinedied/ollamazure PhiSilica - https://learn.microsoft.com/en-us/windows/ai/apis/phi-silica File Shares: https://learn.microsoft.com/en-us/azure/storage/common/storage-introduction Other updates: Lots of AKS updates! https://learn.microsoft.com/en-us/azure/aks/concepts-network-isolated https://learn.microsoft.com/en-us/troubleshoot/azure/azure-kubernetes/availability-performance/container-image-pull-performance https://learn.microsoft.com/en-us/azure/aks/imds-restriction https://learn.microsoft.com/en-us/azure/aks/use-windows-gpu https://azure.microsoft.com/en-us/updates/?id=471295 https://learn.microsoft.com/en-us/azure/backup/tutorial-restore-aks-backups-across-regions https://learn.microsoft.com/en-us/azure/aks/app-routing-nginx-configuration?tabs=azurecli#control-the-default-nginx-ingress-controller-configuration-preview https://learn.microsoft.com/en-us/azure/aks/automated-deployments https://learn.microsoft.com/en-us/azure/aks/aks-extension-ghcopilot-plugins https://learn.microsoft.com/en-us/azure/azure-monitor/containers/container-insights-logs-schema#kubernetes-metadata-and-logs-filtering
Plus AI Workplace Monitoring Faces Backlash Like this? Get AIDAILY, delivered to your inbox, every weekday. Subscribe to our newsletter at https://aidaily.us AI Influencers Drive Traffic to Adult Content Platforms AI-generated influencers are being used to direct traffic to adult content platforms like OnlyFans and Fanvue, where more AI content awaits. Some accounts feature deepfakes or face-swapped images, sparking ethical concerns. While AI expands content possibilities, real-life creators worry about competition and eroding trust, as fans often fail to recognize these "people" are artificial. AI Workplace Monitoring Sparks Fears of Dystopian Surveillance A controversial AI-powered productivity software tracks employees' every move, creating detailed metrics and suggesting automation replacements. Features include keylogging, heatmaps, and "productivity graphs" that flag underperformers for managerial review. Critics label the software dystopian, fearing it promotes system gaming and job insecurity, accelerating automation's impact on the workforce. Gen Z Leads the Way in Workplace AI Adoption A Google Workspace survey shows 93% of Gen Z workers (ages 22-27) use two or more AI tools weekly, far outpacing millennials. Tools like ChatGPT and Otter.ai help with tasks such as revising emails and taking meeting notes. While younger workers embrace AI openly, broader adoption remains slow, raising productivity and job loss questions. Robert Kiyosaki Predicts $500K Bitcoin by 2025 Using AI Investor Robert Kiyosaki forecasts Bitcoin reaching $500,000 in 2025, based on an unnamed AI platform. While previous predictions, like $350,000 for August 2024, fell short, his bullish stance on Bitcoin and diverse investments has yielded significant returns. A $1,000 portfolio following his advice in early 2024 grew by 76% within 11 months. YouTube Shorts Unveils AI-Generated Video Backgrounds YouTube Shorts' Dream Screen now enables creators to generate AI-powered video backdrops using Google DeepMind's Veo model. Users can craft 1080p cinematic scenes from text prompts, enhancing storytelling and creative possibilities. This innovation, outpacing TikTok's image-only AI backgrounds, positions YouTube as a leader in short-form video content. Small Language Models (SLMs): The Future of Tailored AI Small Language Models (SLMs) are emerging as efficient alternatives to Large Language Models (LLMs), offering targeted, cost-effective solutions. With reduced energy demands and greater data control, SLMs excel in fields like customer service, healthcare, and finance. Domain-specific models further enhance accuracy, presenting businesses with scalable, trusted AI tailored to specific needs.
E143: David updates listeners on Venture for the week, then interviews Josh Miller of Gradient Health about his take on AI from the perspective of data. We discuss his data experience in the context of AI model training and validation, and address some timely questions relevant to the current Era of AI: 1) Is Data where the money is (in addition to GPUs) and is there really future profit in AI models? 2) Data quality, structure and annotations for metadata, 3) Are LLMs being commoditized and what is the future of SLMs? 4) What is the future of AI Assistants and Agents? 5) What is the future of Synthetic Data? 6) How will AI affect the Arts? 7) What is the future for AI investment? (recorded 11/1/24)BIP 2024 State of Startups in the Southeast reportFollow David on LinkedIn or reach out to David on Twitter/X @DGRollingSouth for comments. Follow Paul on LinkedIn or reach out to Paul on Twitter/X @PalmettoAngel We invite your feedback and suggestions at www.ventureinthesouth.com or email david@ventureinthesouth.com. Learn more about RollingSouth at rollingsouth.vc or email david@rollingsouth.vc.
Many aspire to having and working a croft, however crofts are difficult to obtain, at least in the more productive and scenic areas. At the same time, retiring crofters sometimes find it hard to give up their business, their source of income and home. The Scottish Land Matching Service is designed to help aspiring new producers, whether crofters or farmers, with advice, guidance, and a database of opportunities. Ian Davidson joins us today to discuss the SLMS role in helping crofts to remain in productive use. Related ResourcesScottish Land Matching Service
Many aspire to having and working a croft, however crofts are difficult to obtain, at least in the more productive and scenic areas. At the same time, retiring crofters sometimes find it hard to give up their business, their source of income and home. The Scottish Land Matching Service is designed to help aspiring new producers, whether crofters or farmers, with advice, guidance, and a database of opportunities. Ian Davidson joins us today to discuss the SLMS role in helping crofts to remain in productive use. Related ResourcesScottish Land Matching Service
With a $4.5B valuation, 5M AI builders and 1M public AI models, Hugging Face has emerged as the key collaboration platform for AI, and the heart of the global open source AI community. In this episode of The MAD Podcast, we sit down with Clément Delangue, its co-founder and CEO, and delve deep into Hugging Face's journey from a fun chatbot to a central hub for AI innovation, the impact of open-source AI and the importance of community-driven development, and discuss the shift from text to other AI modalities like audio, video, chemistry, and biology. We also cover the evolution of Hugging Face's business model, and the different approach to company culture that the founders have implemented over the years. Hugging Face Website - https://huggingface.co Twitter - https://x.com/huggingface Clem Delangue LinkedIn - https://www.linkedin.com/in/clementdelangue Twitter - https://x.com/clemdelangue FIRSTMARK Website - https://firstmark.com Twitter - https://twitter.com/FirstMarkCap Matt Turck (Managing Director) LinkedIn - https://www.linkedin.com/in/turck/ Twitter - https://twitter.com/mattturck (00:00) Intro (01:46) Miami vs. New York vs. San Francisco (03:25) Current state of open source AI (11:12) Government regulation of AI (13:18) What is open source AI? (15:21) Open source AI: China vs U.S. (18:32) LLMs vs. SLMs (22:01) Are commercial LLMs just 'Training Wheels' for enterprises? (24:26) Software 2.0: built with AI (28:03) Hugging Face founding story (37:03) Are there any competitors? (44:06) Most interesting models on Hugging Face (50:35) Shifting focus in enterprise solutions (55:06) Bloom & Idefix (58:44) The culture of Hugging Face (01:04:44) The future of Hugging Face
Send us a textMore on GenAI, Hallucinations, RAG, Use Cases, LLMs, SLMs and costs with Armand Ruiz, Director watsonx Client Engineering and John Webb, Principal Client Engineering. With this and the previous episode you'll be wiser on AI than 98% of the world.00:12 Hallucinations02:33 RAG Differentiation06:41 Why IBM in AI09:23 Use Cases11:02 The GenAI Resume13:37 watson.x 15:40 LLMs17:51 Experience Counts20:03 AI that Surprises23:46 AI Skills26:47 Switching LLMs27:13 The Cost and SLMs28:21 Prompt Engineering29:16 For FunLinkedIn: linkedin.com/in/armand-ruiz, linkedin.com/in/john-webb-686136127 Website: https://www.ibm.com/client-engineeringLove what you're hearing? Don't forget to rate us on your favorite platform!Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
Send us a textMore on GenAI, Hallucinations, RAG, Use Cases, LLMs, SLMs and costs with Armand Ruiz, Director watsonx Client Engineering and John Webb, Principal Client Engineering. With this and the previous episode you'll be wiser on AI than 98% of the world.00:12 Hallucinations02:33 RAG Differentiation06:41 Why IBM in AI09:23 Use Cases11:02 The GenAI Resume13:37 watson.x 15:40 LLMs17:51 Experience Counts20:03 AI that Surprises23:46 AI Skills26:47 Switching LLMs27:13 The Cost and SLMs28:21 Prompt Engineering29:16 For FunLinkedIn: linkedin.com/in/armand-ruiz, linkedin.com/in/john-webb-686136127 Website: https://www.ibm.com/client-engineeringLove what you're hearing? Don't forget to rate us on your favorite platform!Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
In this episode, we explore the impact of Artificial Intelligence (AI) on project management and how it's transforming the profession. Oliver Yarbrough shares how project managers can leverage AI to enhance their skills and stay competitive in an evolving, AI-driven landscape. Hear about AI's impact on Agile teams, how SLMs and LLMs are revolutionizing data refinement, how to balance data security while leveraging AI, and how to treat AI as a key stakeholder in the evolving landscape of project management. Chapters 02:21 … Meet Oliver04:21 … What is AI?05:39 … Will AI Replace the PM?06:41 … Incorporating AI Tools08:45 … Finding the AI Capabilities09:44 … Skills and Knowledge Areas13:02 … AI and Data Analysis Challenges15:23 … ChatGPT and Data16:40 … Human in the Loop18:08 … Protecting Your Data20:14 … Contractors Using AI22:20 … Kevin and Kyle23:18 … Impact on Agile Team Performance26:22 … Fine Tuning and Refining29:05 … A Large Language Model (LLM)30:08 … Current Trends in AI32:21 … AI Component to PM Tools33:40 … Streamlining Workflow with AI39:36 … Future Evolutions of AI43:17 … Contact Oliver44:58 … Closing OLIVER YARBROUGH: AI acts as a stakeholder on our projects, and we should treat it like we treat any other stakeholder. That's very important. Initially, I used to say treat it like it's a piece of software tool. But with the new advents of these AI agents and AI assistants and all these other things, you really do need to treat it like a true stakeholder. WENDY GROUNDS: Welcome to another episode of Manage This. where we dive deep into the latest trends, insights, and strategies in project management. This is the podcast by project managers for project managers. I'm Wendy Grounds, and with me in the studio is Bill Yates. And in the studio today we have an incredible guest who is sure to enlighten, inspire, and, I think for me, educate a lot. Joining us is Oliver Yarbrough. He's a PMP, a renowned author, speaker, and trainer with a knack for combining hands-on real-world experience with project management fundamentals. His impressive career includes positions with Fortune 500 companies like Lucent Technologies, Staples, and Sprint, as well as successful business ventures of his own. Currently, Oliver is an active member of PMI, where he shares his extensive knowledge on adapting to AI, deriving value from data, and recognizing AI trends in project management. He has some LinkedIn courses which we've taken a look at. They cover everything from leveraging AI in project management to the importance of human strengths in an AI-driven world. BILL YATES: As Wendy is saying, we're going to explore a topic that, I mean, if you connect to the news, if you connect to the Internet in any way, probably one of the top trending topics is AI, or artificial intelligence. We're going to dive deep into that with Oliver, and we're going to look at it from a specific lens, and that is from the perspective of the project manager. How does this impact me? How does this impact my job and my future? Oliver is going to share some insights with us. He'll help us understand how to stay relevant. What are some strengths from AI that we can harness? What are some things that we cannot fear? So, Oliver is here to open our minds. WENDY GROUNDS: Yup, so get ready as we welcome Oliver. Hi, Oliver. Welcome to Manage This. OLIVER YARBROUGH: Yes, great. Glad to be here. Meet Oliver WENDY GROUNDS: Oliver, why don't you tell us how you got into artificial intelligence? How you took that path? OLIVER YARBROUGH: Well, I sort of fell into it backwards. So, I did not start off as an AI person. I've always been a Curious George. I've always been poking my head in, like, “What's going on here? What's going on there?” But, you know, I have a project management background. So, I was doing PMP exam prep. I was training people. And that's how I got in touch like with you guys.
In this episode, Doug shares his preference for composition over inheritance in object-oriented programming and his strategic use of design patterns in Visual Basic consulting. He challenges commonly held beliefs about language performance and productivity, arguing that faster languages do not always yield faster results. The conversation also explores the offline benefits of large and small language models (LLMs and SLMs) and highlights Doug's innovative use of PowerShell to create autonomous agents.Doug shares fascinating insights on prompt engineering, the evolution of AI models, and the potential of personal AI as the next technological inflection point. Despite facing resistance from critics and the tech community, Doug remains a staunch advocate for leveraging cutting-edge tools and maintaining an unscripted, adaptive approach to technology.Show NotesTime Stamps07:32 Discovering GPT chat and its incredible capabilities.14:25 Expect announcement at OpenAI Day in November.19:41 Initial confusion, but eventually realized cross-platform potential.25:31 Colleague makes fun of me, but impressed.30:07 Experience of being a non-traditional engineer.35:10 Prefer using PowerShell over Python for coding.40:36 Discussing hallucination problem and algorithms in AI.43:19 Using AI to generate better function names.47:46 "Creating forms quickly with impressive results."54:58 Recall story of new guy at whiskey distillery.01:01:06 Microsoft focuses on smaller, efficient language models.01:08:12 Data-driven podcast explores PowerShell and AI's fusion.LinksPSAI (PowerShell AI module): https://github.com/dfinke/PSAI PSWeave (PowerShell module bringing OpenAI's GPT): https://github.com/dfinke/PSWeaveImportExcel (PowerShell module to import/export Excel spreadsheets): https://github.com/dfinke/ImportExcelNew York PowerShell Meetup: Meetup https://www.meetup.com/nycpowershellmeetup/
Dave Sobel welcomes Anurag Agarwal from TechIsle to discuss research data on customer expectations, cybersecurity, and AI trends. The conversation delves into the increasing budget allocations for IT security among SMBs, highlighting the importance of consulting services in guiding SMBs towards choosing the right security technologies and frameworks. Anurag emphasizes the shift towards cybersecurity as a business risk, prompting SMBs to focus on cyber resiliency rather than just cybersecurity. The discussion then transitions to the evolving landscape of AI adoption, with a focus on large language models (LLMs) and their impact on businesses. Anurag and Dave explore the significance of AI consulting in preparing organizations for AI implementation, emphasizing the need for expertise in selecting the right language models for specific business problems. The conversation underscores the importance of aligning with a single hyperscaler for AI solutions and the emerging trend towards small language models (SLMs) for accelerated AI adoption. Anurag highlights the growing trend of AI assessment as a key focus for both partners and end customers, surpassing cloud cost optimization and security assessments. Supported by: https://salesbuildr.com/ All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessoftech.bsky.social
“Microsoft is making a bet that we're not going to need a single AI, we're going to need many different AIs” Sebastien Bubeck, Microsoft's vice president of generative-AI research, tells Bloomberg senior technology analyst Anurag Rana. In this Tech Disruptors episode, the two examine the differences between a large language model like ChatGPT-4o and a small language model such as Microsoft's Phi-3 family. Bubeck and Rana account for various use cases of the models across various industries and workflows. The two also compare the costs and differences in compute/GPU requirements between SLMs and LLMs.
This episode features the second part of an engaging discussion between Raja Iqbal, Founder and CEO of Data Science Dojo, and Bob van Luijt, Co-founder and CEO of Weaviate, a prominent open-source vector database in the industry. Raja and Bob trace the evolution of AI over the years, the current LLM landscape, and its outlook for the future. They further dive deep into various LLM concepts such as RAG, fine-tuning, challenges in enterprise adoption, vector search, context windows, the potential of SLMs, generative feedback loop, and more. Lastly, Raja and Bob explore Artificial General Intelligence (AGI) and whether it could be a reality in the near future. This episode is a must watch for anyone interested in a comprehensive outlook on the current state and future trajectory of AI.
Tensorraum - Der KI Podcast | News über AI, Machine Learning, LLMs, Tech-Investitionen und Mehr
Passend zur Fußballeuropameisterschaft starten wir in die Folge mit einem KI-Tippspiel: Was glauben ChatGPT, Gemini und weitere, wie das nächste Deutschlandspiel ausgeht? Dann gehen wir aber direkt zu ernsten Themen über: Der Google-Forscher François Chollet sagte in einem NZZ Interview im April, dass die Investitionen in GenAI-Entwicklungen 1000-fach (!) zu hoch seien. Was ist dran an seiner These? Die Unternehmensberatung PwC hat sich währenddessen mit Aleph Alpha zusammengetan, um mit der creance.ai einen virtuellen Anwalt zu entwickeln. Erste Studien zu solchen Anwendungen zeigen jedoch, dass noch viel Arbeit in die Modelle gesteckt werden muss. Etwas mehr Zeit nehmen wir uns um auf den aktuellen Report von Lucidworks zu schauen: “The State of Generative AI in 2024”. Abschließend experimentieren wir mit dem neuesten Text-to-Video Modell lumalabs Dream Machine. Links zur Folge: Google-Forscher zu KI-Hype in der Wirtschaft: «Die Investitionen sind um ein Tausendfaches zu hoch» PwC Germany and Aleph Alpha launch founded joint venture creance.ai AI on Trial: Legal Models Hallucinate in 1 out of 6 (or More) Benchmarking Queries The State of Generative AI in 2024: Benchmarking the Hype vs. Reality lumalabs Dream Machine Gebt uns gerne Feedback Email: info@tensorraum.de Links zu uns: https://www.tensorraum.de Hosts: Stefan Wiezorek: https://www.linkedin.com/in/stefanwiezorek/ Dr. Arne Meyer: https://www.linkedin.com/in/arne-meyer-6a36612b9/ Dr. Jannis Buchsteiner: https://www.linkedin.com/in/jannis-buchsteiner/ Kapitelmarken: 00:00:00 Anfang und Teaser 00:02:11 KI-Tippspiel zur EM 00:05:12 François Chollet: KI-Investitionen zu hoch 00:11:44 AlphaFold: missglückte Monetarisierung? 00:18:42 PwC und Aleph Alpha stellen creance.ai vor 00:24:33 SLMs für Fachbereiche vs LLMS 00:34:40 Lucidworks: The State of Generative AI in 2024 00:49:38 Text-to-Video: lumalabs Dream Machine 00:57:43 Abschluss und Ausblick
Windows 11 A quick look back at the Copilot+ PC launch Paul did end up making a video of each MacBook Air reference during last week's launch The Copilot+ PC event was also notable for its many references to the past: Paul counted at least 7 in the first 7 minutes alone After some soul-searching, Paul went all-in on Surface Laptop by canceling the first preorder and bulking it up with more RAM and storage Release Preview (last week): 24H2 comes to RP, suggesting it hits stable on Tuesday, June 11 (in preview), one week before the first Copilot+ PCs arrive with this build preinstalled Beta (last week): 23H2 build with no new features (arriving after 24H2 in Release Preview, of course) Microsoft Edge is getting more responsive thanks to a "WebUI 2.0" initiative Lenovo earnings up 9 percent in quarter, down 8 percent for the year. The future? AI PCs, duh AI There was a massive Bing outage late last week. Press hold on all the obvious jokes, this impacted Copilot everywhere, DuckDuckGo, other services Cue the Chicken Little "this is why I'll never use AI" crowd, which used to be the "this is why I'll never use the cloud" crowd Copilot comes to Telegram for some reason Google goes live with AI overviews in Search and the world grinds to a halt Google adds Gemini to Chromebook Plus, gives one free year of Google One AI Premium to new device buyers WWDC is coming soon and we're seeing hints of how Apple will add more AI to its products Opera partners with Google Cloud on Gemini in Aria AI and image understanding/image generation in browser And it now plans to make 2000 SLMs available in the browser NVIDIA revenues were a record in Q1, up 262 percent YOY Dev Last week, we learned that WPF is making a comeback. This week, Paul revived his .NETpad project and is going to modernize it using the new features Xbox We finally have some news about Activision Blizzard games and Game Pass!!! But it's only one game, and it doesn't happen until November Atari buys the Intellivision brand. I wish we knew more about this Tips & Picks Tip of the week: Beware the dark patterns App pick of the week: Windows 11 version 24H2 RunAs Radio this week: PowerApp Extensibility with Christina Wheeler Brown liquor pick of the week: Glen Garioch 1797 Founder's Reserve Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: HP.com - WW - https://bit.ly/4adilko GO.ACILEARNING.COM/TWIT - code TWIT30
Bing outage, NVIDIA's record Q1 FY25, WPF's rebirth Windows 11 A quick look back at the Copilot+ PC launch Paul did end up making a video of each MacBook Air reference during last week's launch The Copilot+ PC event was also notable for its many references to the past: Paul counted at least 7 in the first 7 minutes alone After some soul-searching, Paul went all-in on Surface Laptop by canceling the first preorder and bulking it up with more RAM and storage Release Preview (last week): 24H2 comes to RP, suggesting it hits stable on Tuesday, June 11 (in preview), one week before the first Copilot+ PCs arrive with this build preinstalled Beta (last week): 23H2 build with no new features (arriving after 24H2 in Release Preview, of course) Microsoft Edge is getting more responsive thanks to a "WebUI 2.0" initiative Lenovo earnings up 9 percent in quarter, down 8 percent for the year. The future? AI PCs, duh AI There was a massive Bing outage late last week. Press hold on all the obvious jokes, this impacted Copilot everywhere, DuckDuckGo, other services Cue the Chicken Little "this is why I'll never use AI" crowd, which used to be the "this is why I'll never use the cloud" crowd Copilot comes to Telegram for some reason Google goes live with AI overviews in Search and the world grinds to a halt Google adds Gemini to Chromebook Plus, gives one free year of Google One AI Premium to new device buyers WWDC is coming soon and we're seeing hints of how Apple will add more AI to its products Opera partners with Google Cloud on Gemini in Aria AI and image understanding/image generation in browser And it now plans to make 2000 SLMs available in the browser NVIDIA revenues were a record in Q1, up 262 percent YOY Dev Last week, we learned that WPF is making a comeback. This week, Paul revived his .NETpad project and is going to modernize it using the new features Xbox We finally have some news about Activision Blizzard games and Game Pass!!! But it's only one game, and it doesn't happen until November Atari buys the Intellivision brand. I wish we knew more about this Tips & Picks Tip of the week: Beware the dark patterns App pick of the week: Windows 11 version 24H2 RunAs Radio this week: PowerApp Extensibility with Christina Wheeler Brown liquor pick of the week: Glen Garioch 1797 Founder's Reserve Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: HP.com - WW - https://bit.ly/4adilko GO.ACILEARNING.COM/TWIT - code TWIT30
Bing outage, NVIDIA's record Q1 FY25, WPF's rebirth Windows 11 A quick look back at the Copilot+ PC launch Paul did end up making a video of each MacBook Air reference during last week's launch The Copilot+ PC event was also notable for its many references to the past: Paul counted at least 7 in the first 7 minutes alone After some soul-searching, Paul went all-in on Surface Laptop by canceling the first preorder and bulking it up with more RAM and storage Release Preview (last week): 24H2 comes to RP, suggesting it hits stable on Tuesday, June 11 (in preview), one week before the first Copilot+ PCs arrive with this build preinstalled Beta (last week): 23H2 build with no new features (arriving after 24H2 in Release Preview, of course) Microsoft Edge is getting more responsive thanks to a "WebUI 2.0" initiative Lenovo earnings up 9 percent in quarter, down 8 percent for the year. The future? AI PCs, duh AI There was a massive Bing outage late last week. Press hold on all the obvious jokes, this impacted Copilot everywhere, DuckDuckGo, other services Cue the Chicken Little "this is why I'll never use AI" crowd, which used to be the "this is why I'll never use the cloud" crowd Copilot comes to Telegram for some reason Google goes live with AI overviews in Search and the world grinds to a halt Google adds Gemini to Chromebook Plus, gives one free year of Google One AI Premium to new device buyers WWDC is coming soon and we're seeing hints of how Apple will add more AI to its products Opera partners with Google Cloud on Gemini in Aria AI and image understanding/image generation in browser And it now plans to make 2000 SLMs available in the browser NVIDIA revenues were a record in Q1, up 262 percent YOY Dev Last week, we learned that WPF is making a comeback. This week, Paul revived his .NETpad project and is going to modernize it using the new features Xbox We finally have some news about Activision Blizzard games and Game Pass!!! But it's only one game, and it doesn't happen until November Atari buys the Intellivision brand. I wish we knew more about this Tips & Picks Tip of the week: Beware the dark patterns App pick of the week: Windows 11 version 24H2 RunAs Radio this week: PowerApp Extensibility with Christina Wheeler Brown liquor pick of the week: Glen Garioch 1797 Founder's Reserve Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: HP.com - WW - https://bit.ly/4adilko GO.ACILEARNING.COM/TWIT - code TWIT30
Windows 11 A quick look back at the Copilot+ PC launch Paul did end up making a video of each MacBook Air reference during last week's launch The Copilot+ PC event was also notable for its many references to the past: Paul counted at least 7 in the first 7 minutes alone After some soul-searching, Paul went all-in on Surface Laptop by canceling the first preorder and bulking it up with more RAM and storage Release Preview (last week): 24H2 comes to RP, suggesting it hits stable on Tuesday, June 11 (in preview), one week before the first Copilot+ PCs arrive with this build preinstalled Beta (last week): 23H2 build with no new features (arriving after 24H2 in Release Preview, of course) Microsoft Edge is getting more responsive thanks to a "WebUI 2.0" initiative Lenovo earnings up 9 percent in quarter, down 8 percent for the year. The future? AI PCs, duh AI There was a massive Bing outage late last week. Press hold on all the obvious jokes, this impacted Copilot everywhere, DuckDuckGo, other services Cue the Chicken Little "this is why I'll never use AI" crowd, which used to be the "this is why I'll never use the cloud" crowd Copilot comes to Telegram for some reason Google goes live with AI overviews in Search and the world grinds to a halt Google adds Gemini to Chromebook Plus, gives one free year of Google One AI Premium to new device buyers WWDC is coming soon and we're seeing hints of how Apple will add more AI to its products Opera partners with Google Cloud on Gemini in Aria AI and image understanding/image generation in browser And it now plans to make 2000 SLMs available in the browser NVIDIA revenues were a record in Q1, up 262 percent YOY Dev Last week, we learned that WPF is making a comeback. This week, Paul revived his .NETpad project and is going to modernize it using the new features Xbox We finally have some news about Activision Blizzard games and Game Pass!!! But it's only one game, and it doesn't happen until November Atari buys the Intellivision brand. I wish we knew more about this Tips & Picks Tip of the week: Beware the dark patterns App pick of the week: Windows 11 version 24H2 RunAs Radio this week: PowerApp Extensibility with Christina Wheeler Brown liquor pick of the week: Glen Garioch 1797 Founder's Reserve Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: HP.com - WW - https://bit.ly/4adilko GO.ACILEARNING.COM/TWIT - code TWIT30
Bing outage, NVIDIA's record Q1 FY25, WPF's rebirth Windows 11 A quick look back at the Copilot+ PC launch Paul did end up making a video of each MacBook Air reference during last week's launch The Copilot+ PC event was also notable for its many references to the past: Paul counted at least 7 in the first 7 minutes alone After some soul-searching, Paul went all-in on Surface Laptop by canceling the first preorder and bulking it up with more RAM and storage Release Preview (last week): 24H2 comes to RP, suggesting it hits stable on Tuesday, June 11 (in preview), one week before the first Copilot+ PCs arrive with this build preinstalled Beta (last week): 23H2 build with no new features (arriving after 24H2 in Release Preview, of course) Microsoft Edge is getting more responsive thanks to a "WebUI 2.0" initiative Lenovo earnings up 9 percent in quarter, down 8 percent for the year. The future? AI PCs, duh AI There was a massive Bing outage late last week. Press hold on all the obvious jokes, this impacted Copilot everywhere, DuckDuckGo, other services Cue the Chicken Little "this is why I'll never use AI" crowd, which used to be the "this is why I'll never use the cloud" crowd Copilot comes to Telegram for some reason Google goes live with AI overviews in Search and the world grinds to a halt Google adds Gemini to Chromebook Plus, gives one free year of Google One AI Premium to new device buyers WWDC is coming soon and we're seeing hints of how Apple will add more AI to its products Opera partners with Google Cloud on Gemini in Aria AI and image understanding/image generation in browser And it now plans to make 2000 SLMs available in the browser NVIDIA revenues were a record in Q1, up 262 percent YOY Dev Last week, we learned that WPF is making a comeback. This week, Paul revived his .NETpad project and is going to modernize it using the new features Xbox We finally have some news about Activision Blizzard games and Game Pass!!! But it's only one game, and it doesn't happen until November Atari buys the Intellivision brand. I wish we knew more about this Tips & Picks Tip of the week: Beware the dark patterns App pick of the week: Windows 11 version 24H2 RunAs Radio this week: PowerApp Extensibility with Christina Wheeler Brown liquor pick of the week: Glen Garioch 1797 Founder's Reserve Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: HP.com - WW - https://bit.ly/4adilko GO.ACILEARNING.COM/TWIT - code TWIT30
Bing outage, NVIDIA's record Q1 FY25, WPF's rebirth Windows 11 A quick look back at the Copilot+ PC launch Paul did end up making a video of each MacBook Air reference during last week's launch The Copilot+ PC event was also notable for its many references to the past: Paul counted at least 7 in the first 7 minutes alone After some soul-searching, Paul went all-in on Surface Laptop by canceling the first preorder and bulking it up with more RAM and storage Release Preview (last week): 24H2 comes to RP, suggesting it hits stable on Tuesday, June 11 (in preview), one week before the first Copilot+ PCs arrive with this build preinstalled Beta (last week): 23H2 build with no new features (arriving after 24H2 in Release Preview, of course) Microsoft Edge is getting more responsive thanks to a "WebUI 2.0" initiative Lenovo earnings up 9 percent in quarter, down 8 percent for the year. The future? AI PCs, duh AI There was a massive Bing outage late last week. Press hold on all the obvious jokes, this impacted Copilot everywhere, DuckDuckGo, other services Cue the Chicken Little "this is why I'll never use AI" crowd, which used to be the "this is why I'll never use the cloud" crowd Copilot comes to Telegram for some reason Google goes live with AI overviews in Search and the world grinds to a halt Google adds Gemini to Chromebook Plus, gives one free year of Google One AI Premium to new device buyers WWDC is coming soon and we're seeing hints of how Apple will add more AI to its products Opera partners with Google Cloud on Gemini in Aria AI and image understanding/image generation in browser And it now plans to make 2000 SLMs available in the browser NVIDIA revenues were a record in Q1, up 262 percent YOY Dev Last week, we learned that WPF is making a comeback. This week, Paul revived his .NETpad project and is going to modernize it using the new features Xbox We finally have some news about Activision Blizzard games and Game Pass!!! But it's only one game, and it doesn't happen until November Atari buys the Intellivision brand. I wish we knew more about this Tips & Picks Tip of the week: Beware the dark patterns App pick of the week: Windows 11 version 24H2 RunAs Radio this week: PowerApp Extensibility with Christina Wheeler Brown liquor pick of the week: Glen Garioch 1797 Founder's Reserve Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: HP.com - WW - https://bit.ly/4adilko GO.ACILEARNING.COM/TWIT - code TWIT30
Microsoft has built the world's largest cloud-based AI supercomputer that is already exponentially bigger than it was just 6 months ago, paving the way for a future with agentic systems. For example, its AI infrastructure is capable of training and inferencing the most sophisticated large language models at massive scale on Azure. In parallel, Microsoft is also developing some of the most compact small language models with Phi-3, capable of running offline on your mobile phone. Watch Azure CTO and Microsoft Technical Fellow Mark Russinovich demonstrate this hands-on and go into the mechanics of how Microsoft is able to optimize and deliver performance with its AI infrastructure to run AI workloads of any size efficiently on a global scale. This includes a look at: how it designs its AI systems to take a modular and scalable approach to running a diverse set of hardware including the latest GPUs from industry leaders as well as Microsoft's own silicon innovations; the work to develop a common interoperability layer for GPUs and AI accelerators, and its work to develop its own state-of-the-art AI-optimized hardware and software architecture to run its own commercial services like Microsoft Copilot and more. ► QUICK LINKS: 00:00 - AI Supercomputer 01:51 - Azure optimized for inference 02:41 - Small Language Models (SLMs) 03:31 - Phi-3 family of SLMs 05:03 - How to choose between SLM & LLM 06:04 - Large Language Models (LLMs) 07:47 - Our work with Maia 08:52 - Liquid cooled system for AI workloads 09:48 - Sustainability commitments 10:15 - Move between GPUs without rewriting code or building custom kernels. 11:22 - Run the same underlying models and code on Maia silicon 12:30 - Swap LLMs or specialized models with others13:38 - Fine-tune an LLM 14:15 - Wrap up ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics
Rob Ocel and Jerome Hardaway continue their series on AI adoption. In this installment, they discuss the differences between small language models (SLMs) and large language models (LLMs), highlighting the unique strengths of each. They also explore the advancements in AI chips by tech giants like Apple and Google, and their potential impact on the industry for developers. The conversation touches on the evolving role of engineers in relation to AI, the role of the software engineer in the AI age, and some ethical implications of AI implementation. Sponsored by This Dot Watch this episode on YouTube Read more on our blog
SummaryChris Gully discusses his current role in the new Broadcom organization and highlights of his career. He emphasizes the importance of staying relevant in the technology industry and the value of working with cool and smart people. The conversation then shifts to the topic of small language models (SLMs) and their role in the landscape of gen AI applications. Gully explains that SLMs offer a more progressive approach to working with large language models (LLMs) and enable more efficient and scalable deployments. The discussion also touches on the components of gen AI applications, the need for right-sizing models, and the challenges of scalability and efficiency. Gully highlights the importance of data and its role in driving business outcomes through AI. The conversation concludes with a discussion on the benefits and limitations of fine-tuning LLMs and the potential future of SLMs. The conversation explores the concept of SLMs (Small Language Models) and their role in AI development. It discusses the advantages of SLMs over LLMs (Large Language Models) regarding efficiency, optimization, and governance. The conversation also touches on the challenges of infrastructure management and resource allocation in AI deployments. It highlights the importance of right-sizing workloads, distributing workloads across data centers, and maximizing resource utilization. The conversation concludes with a discussion on the future trends in machine learning and AI, including advancements in math and the need for accessible and efficient technology.LinksVMware's Approach to Private AIMicrosoft Phi-2 - The surprising power of small language modelsMixtralMixtral on HuggingFaceTakeawaysStaying relevant in the technology industry is crucial for career success.Small language models (SLMs) offer a more efficient and scalable approach to working with large language models (LLMs).Data is the most important and untapped asset for organizations, and leveraging it through AI can drive business outcomes.Scalability and efficiency are key challenges in deploying gen AI applications.Fine-tuning LLMs can enhance their precision and reduce the need for extensive training.The future of SLMs may involve dynamic training and efficient distribution to support evolving business needs. SLMs offer advantages in terms of efficiency, optimization, and governance compared to LLMs.Infrastructure management and resource allocation are crucial in AI deployments.Right-sizing workloads and maximizing resource utilization are key considerations.Future trends in machine learning and AI include advancements in math and the need for accessible and efficient technology.Follow us on X for updates and news about upcoming episodes: https://x.com/UnexploredPod.Last but not least, make sure to hit that subscribe button and share the episode with your friends and colleagues!Disclaimer: The thoughts and opinions shared in this podcast are our own/guest(s), and not necessarily those of Broadcom or VMware by Broadcom.
More on GenAI, Hallucinations, RAG, Use Cases, LLMs, SLMs and costs with Armand Ruiz, Director watsonx Client Engineering and John Webb, Principal Client Engineering. With this and the previous episode you'll be wiser on AI than 98% of the world.00:12 Hallucinations02:33 RAG Differentiation06:41 Why IBM in AI09:23 Use Cases11:02 The GenAI Resume13:37 watson.x 15:40 LLMs17:51 Experience Counts20:03 AI that Surprises23:46 AI Skills26:47 Switching LLMs27:13 The Cost and SLMs28:21 Prompt Engineering29:16 For FunLinkedIn: linkedin.com/in/armand-ruiz, linkedin.com/in/john-webb-686136127 Website: https://www.ibm.com/client-engineeringLove what you're hearing? Don't forget to rate us on your favorite platform!Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
More on GenAI, Hallucinations, RAG, Use Cases, LLMs, SLMs and costs with Armand Ruiz, Director watsonx Client Engineering and John Webb, Principal Client Engineering. With this and the previous episode you'll be wiser on AI than 98% of the world.00:12 Hallucinations02:33 RAG Differentiation06:41 Why IBM in AI09:23 Use Cases11:02 The GenAI Resume13:37 watson.x 15:40 LLMs17:51 Experience Counts20:03 AI that Surprises23:46 AI Skills26:47 Switching LLMs27:13 The Cost and SLMs28:21 Prompt Engineering29:16 For FunLinkedIn: linkedin.com/in/armand-ruiz, linkedin.com/in/john-webb-686136127 Website: https://www.ibm.com/client-engineeringLove what you're hearing? Don't forget to rate us on your favorite platform!Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
Google stellt Text-zu-Video KI Lumiere vor Microsoft intensiviert Forschung an effizienteren KI-Modellen SAP setzt auf KI und Firefox integriert KI-Rezensionsprüfer heise.de/ki-update https://www.heise.de/thema/Kuenstliche-Intelligenz https://the-decoder.de/ https://www.heiseplus.de/podcast
In this paper, we present StyleTTS 2, a text-to-speech (TTS) model that leverages style diffusion and adversarial training with large speech language models (SLMs) to achieve human-level TTS synthesis. StyleTTS 2 differs from its predecessor by modeling styles as a latent random variable through diffusion models to generate the most suitable style for the text without requiring reference speech, achieving efficient latent diffusion while benefiting from the diverse speech synthesis offered by diffusion models. Furthermore, we employ large pre-trained SLMs, such as WavLM, as discriminators with our novel differentiable duration modeling for end-to-end training, resulting in improved speech naturalness. StyleTTS 2 surpasses human recordings on the single-speaker LJSpeech dataset and matches it on the multispeaker VCTK dataset as judged by native English speakers. Moreover, when trained on the LibriTTS dataset, our model outperforms previous publicly available models for zero-shot speaker adaptation. This work achieves the first human-level TTS on both single and multispeaker datasets, showcasing the potential of style diffusion and adversarial training with large SLMs. The audio demos and source code are available at https://styletts2.github.io/. 2023: Y. Li, Cong Han, Vinay S. Raghavan, Gavin Mischler, N. Mesgarani https://arxiv.org/pdf/2306.07691v2.pdf
Hey yall, welcome to this special edition of ThursdAI. This is the first one that I'm sending in my new capacity as the AI Evangelist Weights & Biases (on the growth team)I made the announcement last week, but this week is my first official week at W&B, and oh boy... how humbled and excited I was to receive all the inspiring and supporting feedback from the community, friends, colleagues and family
Pronounced Dan-Ton-E-O!What a blast talking with one of the cheeriest people you'll ever meet!
2023 June 4th Race Time Radio (Special Note: June 11th Race Time Radio Time Change to 5PM ET on SiriusXM Canada Talks, plus our YoutTube Channel) With Your Host: Joe Chisholm and Co-Host Joe Chisholm Jr Watch: June 4th 2023: https://www.youtube.com/live/fou3nEDLopY?feature=share ----------------------- Featuring: - Brent Roy talks Super Late Model Series and Speedway 660 - Kyle Steckly of 22 Racing wins pro late model event at Delaware Speedway - Dylan Blenkhorn No.67 talks East Coast Maritime Pro Stock Tour and MASS Late Model Series - Full Throttle Motor Speedway in Varney Ontario, with driver interviews and more - AVION Motorsports RS1 Cup Series raced Area 27 - Plus more racing news coast to coast Special thank you to Full Throttle Motors Speedway for the Hospitality Access To Race Time Radio: Live Stream RaceTimeRadioTV Live: https://www.youtube.com/@racetimeradiotv/streams RaceTimeRadioTV Videos: https://www.youtube.com/@racetimeradiotv/videos Web: http://www.racetimeradio.com Twitter: https://twitter.com/Racetimeradio Facebook: https://www.facebook.com/race.timeradio iTunes: https://itunes.apple.com/ca/podcast/race-time-radio/id1368707581 Missed a Broadcast Catch Up Here:: https://racetimeradio.podbean.com Race Time Radio Fuelled By:: Visit: Qwick Wick https://www.qwickwick.com/ Save $ Use Promo Code: RTR https://www.qwickwick.com/collections/frontpage/products/fire-starters 'Limited Time Offer' Visit: Rev TV: http://revtv.ca/ Visit Napa Auto Parts: - New Glasgow https://www.napacanada.com/en/ns/new-glasgow/store/1006060 - Antigonish: https://www.napacanada.com/en/ns/antigonish/store/1001258 - Port Hawkesbury: https://www.napacanada.com/en/ns/port-hawkesbury/store/1007375 Visit: VP Racing Fuels https://vpontario.com/ Visit: Quality Inn Halifax Airport http://www.airporthotelhalifax.com/ Visit: Dawson Dental http://dawsondental.ca/ Visit: CTMP For Upcoming Race Events https://canadiantiremotorsportpark.com/ Visit: RPM Race Parts https://www.facebook.com/RPM-Race-Parts-103247914650387 Visit: SiriusXM Ch 167 https://www.siriusxm.ca/channels/canada-talks/ Visit: Leaf Racewear https://leafracewear.com/ Plus: Join Us Weekly Sunday Nights Live on RTR Live Stream at 5:00 pm ET or SiriusXM Ch 167 or: On Race Time Radio TV on YouTube: : https://www.youtube.com/@racetimeradiotv/streams (Monday Night On RevTV Canada 4pm ET.)
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: TinyStories: Small Language Models That Still Speak Coherent English, published by Ulisse Mini on May 28, 2023 on LessWrong. Abstract Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely generate coherent and consistent English text beyond a few words even after extensive training. This raises the question of whether the emergence of the ability to produce coherent English text only occurs at larger scales (with hundreds of millions of parameters or more) and complex architectures (with many layers of global attention). In this work, we introduce TinyStories, a synthetic dataset of short stories that only contain words that a typical 3 to 4-year-olds usually understand, generated by GPT-3.5 and GPT-4. We show that TinyStories can be used to train and evaluate LMs that are much smaller than the state-of-the-art models (below 10 million total parameters), or have much simpler architectures (with only one transformer block), yet still produce fluent and consistent stories with several paragraphs that are diverse and have almost perfect grammar, and demonstrate reasoning capabilities. We also introduce a new paradigm for the evaluation of language models: We suggest a framework which uses GPT-4 to grade the content generated by these models as if those were stories written by students and graded by a (human) teacher. This new paradigm overcomes the flaws of standard benchmarks which often requires the model's output to be very structures, and moreover provides a multidimensional score for the model, providing scores for different capabilities such as grammar, creativity and consistency. We hope that TinyStories can facilitate the development, analysis and research of LMs, especially for low-resource or specialized domains, and shed light on the emergence of language capabilities in LMs. Implications Interpretability One part that isn't mentioned in the abstract but is interesting: We show that the trained SLMs appear to be substantially more interpretable than larger ones. When models have a small number of neurons and/or a small number of layers, we observe that both attention heads and MLP neurons have a meaningful function: Attention heads produce very clear attention patterns, with a clear separation between local and semantic heads, and MLP neurons typically activated on tokens that have a clear common role in the sentence. We visualize and analyze the attention and activation maps of the models, and show how they relate to the generation process and the story content. The difference between highly activating tokens for a neuron is striking, here's the tiny model: ...and here's GPT2-XL: Capabilities Again from the introduction (emphasis mine) However, it is currently not clear whether the inability of SLMs to produce coherent text is a result of the intrinsic complexity of natural language, or of the excessive breadth and diversity of the corpora used for training. When we train a model on Wikipedia, for example, we are not only teaching it how to speak English, but also how to encode and retrieve an immense amount of facts and concepts from various domains and disciplines. Could it be that SLMs are overwhelmed by the amount and variety of information they have to process and store, and that this hinders their ability to learn the core mechanisms and principles of language? This raises the question of whether we can design a dataset that preserves the essential elements of natural language, such as grammar, vocabulary, facts, and reasoning, but that is much smaller and more refined in terms of its breadth and diversity. If this is true, there could be ways to drastically cut LLM t...
Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: TinyStories: Small Language Models That Still Speak Coherent English, published by Ulisse Mini on May 28, 2023 on LessWrong. Abstract Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely generate coherent and consistent English text beyond a few words even after extensive training. This raises the question of whether the emergence of the ability to produce coherent English text only occurs at larger scales (with hundreds of millions of parameters or more) and complex architectures (with many layers of global attention). In this work, we introduce TinyStories, a synthetic dataset of short stories that only contain words that a typical 3 to 4-year-olds usually understand, generated by GPT-3.5 and GPT-4. We show that TinyStories can be used to train and evaluate LMs that are much smaller than the state-of-the-art models (below 10 million total parameters), or have much simpler architectures (with only one transformer block), yet still produce fluent and consistent stories with several paragraphs that are diverse and have almost perfect grammar, and demonstrate reasoning capabilities. We also introduce a new paradigm for the evaluation of language models: We suggest a framework which uses GPT-4 to grade the content generated by these models as if those were stories written by students and graded by a (human) teacher. This new paradigm overcomes the flaws of standard benchmarks which often requires the model's output to be very structures, and moreover provides a multidimensional score for the model, providing scores for different capabilities such as grammar, creativity and consistency. We hope that TinyStories can facilitate the development, analysis and research of LMs, especially for low-resource or specialized domains, and shed light on the emergence of language capabilities in LMs. Implications Interpretability One part that isn't mentioned in the abstract but is interesting: We show that the trained SLMs appear to be substantially more interpretable than larger ones. When models have a small number of neurons and/or a small number of layers, we observe that both attention heads and MLP neurons have a meaningful function: Attention heads produce very clear attention patterns, with a clear separation between local and semantic heads, and MLP neurons typically activated on tokens that have a clear common role in the sentence. We visualize and analyze the attention and activation maps of the models, and show how they relate to the generation process and the story content. The difference between highly activating tokens for a neuron is striking, here's the tiny model: ...and here's GPT2-XL: Capabilities Again from the introduction (emphasis mine) However, it is currently not clear whether the inability of SLMs to produce coherent text is a result of the intrinsic complexity of natural language, or of the excessive breadth and diversity of the corpora used for training. When we train a model on Wikipedia, for example, we are not only teaching it how to speak English, but also how to encode and retrieve an immense amount of facts and concepts from various domains and disciplines. Could it be that SLMs are overwhelmed by the amount and variety of information they have to process and store, and that this hinders their ability to learn the core mechanisms and principles of language? This raises the question of whether we can design a dataset that preserves the essential elements of natural language, such as grammar, vocabulary, facts, and reasoning, but that is much smaller and more refined in terms of its breadth and diversity. If this is true, there could be ways to drastically cut LLM t...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: TinyStories: Small Language Models That Still Speak Coherent English, published by Ulisse Mini on May 28, 2023 on The AI Alignment Forum. Abstract Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely generate coherent and consistent English text beyond a few words even after extensive training. This raises the question of whether the emergence of the ability to produce coherent English text only occurs at larger scales (with hundreds of millions of parameters or more) and complex architectures (with many layers of global attention). In this work, we introduce TinyStories, a synthetic dataset of short stories that only contain words that a typical 3 to 4-year-olds usually understand, generated by GPT-3.5 and GPT-4. We show that TinyStories can be used to train and evaluate LMs that are much smaller than the state-of-the-art models (below 10 million total parameters), or have much simpler architectures (with only one transformer block), yet still produce fluent and consistent stories with several paragraphs that are diverse and have almost perfect grammar, and demonstrate reasoning capabilities. We also introduce a new paradigm for the evaluation of language models: We suggest a framework which uses GPT-4 to grade the content generated by these models as if those were stories written by students and graded by a (human) teacher. This new paradigm overcomes the flaws of standard benchmarks which often requires the model's output to be very structures, and moreover provides a multidimensional score for the model, providing scores for different capabilities such as grammar, creativity and consistency. We hope that TinyStories can facilitate the development, analysis and research of LMs, especially for low-resource or specialized domains, and shed light on the emergence of language capabilities in LMs. Implications Interpretability One part that isn't mentioned in the abstract but is interesting: We show that the trained SLMs appear to be substantially more interpretable than larger ones. When models have a small number of neurons and/or a small number of layers, we observe that both attention heads and MLP neurons have a meaningful function: Attention heads produce very clear attention patterns, with a clear separation between local and semantic heads, and MLP neurons typically activated on tokens that have a clear common role in the sentence. We visualize and analyze the attention and activation maps of the models, and show how they relate to the generation process and the story content. The difference between highly activating tokens for a neuron is striking, here's the tiny model: ...and here's GPT2-XL: Capabilities Again from the introduction (emphasis mine) However, it is currently not clear whether the inability of SLMs to produce coherent text is a result of the intrinsic complexity of natural language, or of the excessive breadth and diversity of the corpora used for training. When we train a model on Wikipedia, for example, we are not only teaching it how to speak English, but also how to encode and retrieve an immense amount of facts and concepts from various domains and disciplines. Could it be that SLMs are overwhelmed by the amount and variety of information they have to process and store, and that this hinders their ability to learn the core mechanisms and principles of language? This raises the question of whether we can design a dataset that preserves the essential elements of natural language, such as grammar, vocabulary, facts, and reasoning, but that is much smaller and more refined in terms of its breadth and diversity. If this is true, there could be ways to drastica...
Dec 4th 2022 - Race Time Radio With Your Host: Joe Chisholm & Co-Host Joe Chisholm Jr WATCH Dec. 4th Video Broadcast On YouTube: https://youtu.be/Ev1_kbjLwdQ ----------------------- Featuring: - Brent Roy of Speedway 660 talks new super late model series on East Coast - Mike Garrow Principal Owner and President of REV TV Canada - Gary Elliott The Iron Man celebrates 50 years behind the wheel - Al Lebert talks Avion Motorsports the 2023 RS1 Cup Series news - Snowball Derby & Snowflake event updates Five Flags Speedway Access To Race Time Radio: Live Stream Via: http://racetimeradio.com/live_stream.htm Web: http://www.racetimeradio.com Twitter: https://twitter.com/Racetimeradio Facebook: https://www.facebook.com/race.timeradio iTunes: https://itunes.apple.com/ca/podcast/race-time-radio/id1368707581 RaceTimeRadioTV Live: https://www.youtube.com/@racetimeradiotv/streams RaceTimeRadioTV Videos: https://www.youtube.com/@racetimeradiotv/videos Missed a Broadcast Catch Up Here:: https://racetimeradio.podbean.com Motorsports Links: - https://www.facebook.com/brent.roy.5 - https://www.facebook.com/Speedway660 - https://speedway660.com/ - https://twitter.com/Speedway660 - https://www.facebook.com/PettyInternationalRaceway - https://www.pettyraceway.com/ - https://www.facebook.com/OysterBedSpeedway - https://oysterbedspeedwaypei.ca/ - https://twitter.com/oysterbedspeedw - https://revtv.ca/ - https://www.facebook.com/revtvcanada -https://twitter.com/revtvcanada - https://www.facebook.com/gary.elliott.56 - https://garyelliottmotorsports.com/ - https://www.facebook.com/AvionMotorsports - https://twitter.com/AvionMotorsport - https://www.avionmotorsports.com/ - https://www.5flagsspeedway.com/ - https://twitter.com/5FlagsSpeedway - https://www.facebook.com/5flagsspeedway - https://twitter.com/FiveFlagsSpeed - https://www.5flagsspeedway.com/ - https://www.facebook.com/5flagsspeedway Race Time Radio Fueled By:: Visit: Qwick Wick https://www.qwickwick.com/ Save $ Use Promo Code: RTR https://www.qwickwick.com/collections/frontpage/products/fire-starters 'Limited Time Offer' Visit: Rev TV: http://revtv.ca/ Visit Napa Auto Parts: - New Glasgow https://www.napacanada.com/en/ns/new-glasgow/store/1006060 - Antigonish: https://www.napacanada.com/en/ns/antigonish/store/1001258 - Port Hawkesbury: https://www.napacanada.com/en/ns/port-hawkesbury/store/1007375 Visit: Bobbleheads Canada - http://bobbleheadscanada.ca Visit: VP Racing Fuels https://vpontario.com/ Visit: APX Racewear: https://www.facebook.com/APX-Racewear-241826969293535/?fref=ts Visit: Quality Inn Halifax Airport http://www.airporthotelhalifax.com/ Visit: Dawson Dental http://dawsondental.ca/ Visit: CTMP For Upcoming Race Events https://canadiantiremotorsportpark.com/ Visit: RPM Race Parts https://www.facebook.com/RPM-Race-Parts-103247914650387 Visit: SiriusXM Ch 167 https://www.siriusxm.ca/channels/canada-talks/ Plus: Join Us Weekly Sunday Nights Live on RTR Live Stream at 7:00 pm ET With Open Phone Lines: 1-519-371-7588 Tune-In Live Stream Via: http://www.racetimeradio.com/live_stream.htm or SiriusXM Ch 167 `````````````````````````````````````````````````````````````````
This week is a little different. Rather than an SLMS educator, I got to interview a fellow middle school principal that I have been able to connect with from afar.I hope everyone enjoys this as much as I did!
CRM systems are seldom simple to use, and never created based on a salesperson’s preferences. During our interview with Ani Chiuzan head of customer marketing at Pipedrive we found a salesperson oriented tool that is both. Ani discusses the basics of a CRM system that salespeople like and what separates CRM from Sales Lead Management Software. We discussed: What makes a great CRM system? Why CRM abandoned its original purpose to serve the sales representatives' needs. What is the difference between CRM and SLMS, or is there a difference? What salespeople dislike most about CRM systems. Is Sales Lead Management Software really separated from CRM? About Pipedrive Founded in 2010, Pipedrive is the first CRM platform developed from the salesperson's point of view. Today, Pipedrive is used by sales teams at more than 90,000 companies worldwide. Pipedrive is the top-rated CRM and has offices in Dublin; Lisbon; London; New York; Prague; Tampa/St. Pete; Tallinn and Tartu, Estonia; and, with the acquisition of Mailigen, Riga, Latvia. Learn more at Pipedrive.com. About our Guest Ani Chiuzan Ani Chiuzan is Head of Customer Marketing at Pipedrive, a global sales CRM with more than 90,000 customers worldwide. Ani is a strategic leader and marketer with deep expertise in designing and executing insight-driven marketing strategies supported by rigorous financial expertise. Her 18-years’ experience includes working with B2C, B2B and SaaS organizations across the globe in sectors such as Telecommunications, IT, Retail, Finance across Europe, Australia, Asia, Africa, US and the Caribbean. Prior company experience includes EE Telecommunications, Velti and Barclaycards. SLMA Radio is hosted by James Obermayer of Funnel Media Group which is a program on the Funnel Radio Channel. Funnel Media Group is the sponsor of SLMA Radio
There has been a steady drum-beat of an emerging category of software to manage sales leads. The category is Sales Lead Management. While Sales Lead Management is a big tent that encompasses many different disciplines and tools, if you search for the category of sales lead management software there are new entrants that say they aren’t CRM. Or are they? Are these “entrants” just CRM companies that separate themselves from a crowded field? Our guest today is Ani Chiuzan head of customer marketing at Pipedrive. Ani discusses the basics of a CRM system that salespeople like and what separates CRM from Sales Lead Management Software. We discussed: Why CRM abandoned its original purpose to serve the sales representatives' needs. What makes a great CRM system What salespeople dislike most about CRM systems Is Sales Lead Management Software really separated from CRM? What is the difference between CRM and SLMS, or is there a difference? About our Guest Ani Chiuzan Ani Chiuzan is Head of Customer Marketing at Pipedrive, a global sales CRM with more than 90,000 customers worldwide. Ani is a strategic leader and marketer with deep expertise in designing and executing insight-driven marketing strategies supported by rigorous financial expertise. Her 18-years’ experience includes working with B2C, B2B and SaaS organizations across the globe in sectors such as Telecommunications, IT, Retail, Finance across Europe, Australia, Asia, Africa, US and the Caribbean. Prior company experience includes EE Telecommunications, Velti and Barclaycards. About Pipedrive Founded in 2010, Pipedrive is the first CRM platform developed from the salesperson's point of view. Today, Pipedrive is used by sales teams at more than 90,000 companies worldwide. Pipedrive is the top-rated CRM and has offices in Dublin; Lisbon; London; New York; Prague; Tampa/St. Pete; Tallinn and Tartu, Estonia; and, with the acquisition of Mailigen, Riga, Latvia. Learn more at Pipedrive.com. ___________________________________________ SLMA Radio is hosted by James Obermayer of Funnel Media Group which is a program on the Funnel Radio Channel. Funnel Media Group is the sponsor of SLMA Radio
Our new art teacher and a former SLMS student!
Our go-to guest teacher here at SLMS and across the Fife School district. She is currently the long-term sub in Mrs. Mendoza's class. Ms. Woodworth always has a smile on her face and a great attitude for kids!
I know you'll enjoy this episode. If you're dating and are open to meeting the right partner or you're in a relationship that you want to make last, these truths are for you. If you like Smart Love Moves tell us about it. Leave a comment below and give SLMs a 5-star rating. Welcome to the Smart Love Moves Family! XOX, Elsie
Our office manager and the friendly voice you usually hear when you call SLMS, Ms. Reiser is this week's reluctant guest!
The Connections teacher from our Glacier team and an absolute legend of SLMS!
The Pipeliners Podcast is pleased to welcome first-time guest Yogi Schulz of Corvelle Consulting to discuss the key elements of a SLMS (Safety and Loss Management System) in Canada. You will learn about the differences between pipeline regulations in the U.S. and Canada, the importance of collecting evidence that supports “assurance” for compliance purposes, and how to determine the appropriate audit support for all size pipeline operations. Listen for valuable insight to apply directly to your role!
This is where all the amazing Fife Music starts! I get to chat with Mr. Miles our SLMS music teacher this week.
Biz and Brian catch up on the new school, discussing interactive white boards, Teams, and the SLMS on the school website. Thanks for listening! In order to receive professional development points listen to this podcast as well as episode 8, register in the ERO with SRN 201818001102802 and fill out this form.
The first smiling face you see when you enter SLMS. Ms. Greer our attendance secretary!
Mrs. Gallwas is our assistant principal at SLMS.
While there's no extended lap-counts for the SLMs or Troos tonight (those will come on their finale weekend!) both divisions put on competitive races, while the dirt modified championship race tightens up between the top 5! Dirtfield Racing
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