Eye On A.I.

Dmitry Shapiro, AI specialist and barrier breaker, discusses the groundbreaking concept of YouAi, a company revolutionizing AI interaction. He reveals how AI can personalize education and introduces Mind Studio, a no code AI tool. Other topics include AI tools for parenting, choosing the best language model, and the challenges of discovering AI models.

Dan O'Connell, Chief AI and Strategy Officer at Dialpad, discusses how AI is transforming business communications. Topics include real-time transcription, sentiment analysis, virtual agents, AI's impact on CRM, chatbot evolution, and cost-effective AI management.

Raul Martynek, CEO of Data Bank, discusses the history and significance of data centers and their role in today's data-driven world. They explore how AI is driving the demand for data center capacity, the challenges faced by the industry, and China's plans to bolster its semiconductor industry. They also delve into the critical issue of power consumption driven by AI and its effects on global power grids.

Diaa El All, founder and CEO of Soundful, discusses how AI is revolutionizing music production and licensing. Soundful's AI tool generates royalty free background music, enabling creators to monetize their content without copyright concerns. They delve into the transformative power of AI in reshaping the music industry, exploring AI-generated music and the legal implications. They also discuss the concept of one shots in music production and Soundful's plans for a mobile app and partnerships with other AI platforms.

Alex Zhavoronkov, CEO of Insilico Medicine, discusses the use of AI in drug discovery and longevity. Topics include Insilico Medicine's tools for hypothesizing protein targets, their automated robotic lab in China, the challenges in the pharmaceutical industry, and the broader implications of tackling aging.

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. Download NetSuite's popular KPI Checklist, designed to give you consistently excellent performance - absolutely free, at NetSuite.com/EYEONAI. On episode #133 of the Eye on AI podcast, Craig Smith sits down with Michael Jordan. A revered scientist and distinguished professor at the University of California, Berkeley, Michael's expertise spans machine learning, statistics, and artificial intelligence. In this episode we explore the intricate landscape of deep learning, its statistical bedrock, and the myriad applications of machine learning methods. We dig deeper into the cloud computing revolution, ignited by deep learning, which has empowered behemoths like Amazon to streamline their logistics and commerce data. The dialogue continues as we uncover the trends in deep learning, its role in the grand scheme of AI, and the persisting challenges in the domain. We conclude by contemplating the repercussions of AI and optimization in complex systems. We examine its historical roots in the mid-20th century, its potential to replace jobs, and its application in various sectors such as financial markets, healthcare, and education. (00:00) Preview (01:00) Introduction (01:36) NetSuite by Oracle (03:53) Deep Learning Advancements in AI (12:56) AI Optimization in Complex Systems (28:53) Future of Machine Learning in Healthcare (39:45) Privacy and Value in Multi-Agent Learning (54:48) Learning Systems, Avatars, and Music Business (1:02:20) Single Source of Truth for Business Owners (1:04:28) NetSuite by Oracle Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

On episode #132 of the Eye on AI podcast, Craig Smith sits down with Scott Downes, Chief Technology Officer at Invisible Technologies. We crack open the fascinating world of large language models (LLMs). What are the unique ways LLMs can revolutionize text cleanup, product classification, and more? Scott unpacks the power of technology like Reinforcement Learning for Human Feedback (RLHF) that expands the horizons of data collection. This podcast is a thorough analysis of the world of language and meaning. How does language encode meaning? Can RLHF be the panacea for complex conundrums? Scott breaks down his vision about using RLHF to redefine problem-solving. We dive into the vexing concept of teaching a language model through reinforcement learning without a world model. We discuss the future of the human workforce in AI, hear Scott's insights on the potential shift from labellers to RLHF workers. What implications does this shift hold? Can AI elevate people to work on more complicated tasks? From exploring the economic pressure companies face to the potential for increased productivity from AI, we break down the future of work. (00:00) Preview and introduction (01:33) Generative AI's Dirty Little Secret (17:33) Large Language Models in Problem Solving (23:24) Large Language Models and RLHF Challenges (30:07) Teaching Language Models Through RLHF(35:35) Language Models' Power and Potential(53:00) Future of Human Workforce in AI(1:03:10) AI Changing Your World Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

Welcome to episode #131 of the Eye on AI podcast with Andrew Ng. Get ready to challenge your perspectives as we sit down with Andrew Ng. We navigate the widely disputed topic of AI as a potential existential threat, with Andrew assuring us that, with time and global cooperation, safety measures can be built to prevent disaster. He offers insight into the debates surrounding the harm AI might cause, including the notions of AI as a bio-weapon and the notorious 'paper clip argument'. Listen as Andrew debunks these theories, delivering an interesting argument for why he believes the associated risks are minimal.Onwards, we venture into the intriguing realm of AI's capability to understand the world, setting the stage for a conversation on how we can objectively assess their comprehension. We explore the safety measures of AI, drawing parallels with the rigour of the aviation industry, and contemplate on the consensus within the research community regarding the danger posed by AI. (00:00) Preview (01:08) Introduction (02:15) Existential risk of artificial intelligence (05:50) Aviation analogy with artificial intelligence (10:00) The threat of AI & deep learning (13:15) Lack of consensus in AI dangers (18:00) How AI can solve climate change (24:00) Landing AI and Andrew Ng (27:30) Visual prompting for images Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI Our sponsor for this episode is Masterworks, an art investing platform. They buy the art outright, from contemporary masters like Picasso and Banksy, then qualify it with the SEC, and offer it as an investment. Net proceeds from its sale are distributed to its investors. Since their inception, they have sold over $45 million dollars worth of artwork And so far, each of Masterworks' exits have returned positive net returns to their investors. Masterworks has over 750,000 users, and their art offerings usually sell out in hours, which is why they've had to make a waitlist. But Eye on AI viewers can skip the line and get priority access right now by clicking this link: https://www.masterworks.art/eyeonai Purchase shares in great masterpieces from artists like Pablo Picasso, Banksy, Andy Warhol, and more. See important Masterworks disclosures: https://www.masterworks.com/cd "Net Return" refers to the annualized internal rate of return net of all fees and costs, calculated from the offering closing date to the date the sale is consummated. IRR may not be indicative of Masterworks paintings not yet sold and past performance is not indicative of future results. Returns shown are 4 examples of midrange returns selected to demonstrate Masterworks performance history. Returns may be higher or lower. Investing involves risk, including loss of principal.

Welcome to episode #130 of Eye on AI with Mathew Lodge. In this episode, we explore the world of reinforcement learning and code generation. Mathew Lodge, the CEO of Diffblue, shares insights into how reinforcement learning fuels generative AI. As we explore the intricacies of reinforcement learning, we uncover its potential in game playing and guiding us towards solutions. We shed light on the products that it powers, such as AlphaGo and AlphaDev. However, we also address the challenges of large language models and explain why they may not be the ultimate solution for code generation. In the last part of our conversation, we delve into the future of language models and intelligence. Mathew shares valuable insights on merging no-code and low-code solutions. We confront the skepticism of software developers towards AI for code products and the task of articulating program outcomes. Wrapping up, we reflect on the evolution of programming languages and the impact of abstraction on machine learning. (00:00) Preview & sponsorship (01:51) Reinforcement Learning and Code Generation (04:39) Reinforcement Learning and Improving Algorithms (15:32) The Challenges of Large Language Models(23:58) Future of Language Models and Intelligence (35:50) Challenges and Potential of AI-generated Code (48:32) Programming Language Evolution and Higher-Level Languages Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

Welcome to episode #129 of Eye on AI with Alexandra Geese. Navigating the complex waters of the European Union's AI Act is no simple task. Yet, that's exactly what Alexandra Geese, a member of the European Parliament, and I venture to do in this conversation. Alexandra's insights into the AI Act, its four defined categories of AI applications, and its current negotiation phase with the European Council and the European Commission are illuminating. We delve into the Act's essential mission: ensuring AI serves humanity, while also exploring the influence of powerful players in the AI industry on the EU's legislation. As our journey deepens, we tackle a range of crucial issues underpinning the Act. Alexandra and navigate through potential economic implications for those who rely on copyright legislation, and the risk of Europe falling behind in AI implementation if the Act is too restrictive. We also touch on the involvement of major American AI firms in the Act's finalization process, and implications for copyrighted material. We dive into the ongoing debates shaping the legislation and the enforcement of the law, once passed. Alexandra shares her thoughts on potential fines for violations, different AI zones, and the possibility of the US following Europe's lead in AI legislation. We wrap up with a deep reflection on the environmental impact of AI, the power held by few companies, and our collective responsibility as AI reshapes the world. (00:00) Preview (00:52) Introduction (03:10) Alexandra Geese background in digital legislation (04:00) The AI act: the explanation and details (08:00) The foundations of corporations for AI regulation (13:00) Copyright regulation and impacts of creativity (17:00) We need AI that serves humanity (21:30) Are foundation models high risk to society? (25:00) Should people be worried about investing in AI? (30:45) What is dynamic AI regulation? (36:10) What is the timeline for AI regulation? (38:50) What penalties will be applied to AI regulation? (44:30) Will US & EU merge on AI regulation? (50:30) How to solve AI hallucinations Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI Found is a show about founders and company-building that features the change-makers and innovators who are actually doing the work. Each week, TechCrunch Plus reporters, Becca Szkutak and Dom-Madori Davis talk with a founder about what it's really like to build and run a company—from ideation to launch. They talk to founders across many industries and their conversations often lead back to AI as many startups start to implement AI into what they do. New episodes of Found are published every Tuesday and you can find them wherever you listen to podcasts. Found podcast: https://podlink.com/found