Meta’s Chief AI Scientist Yann LeCun is considered one of the “Godfathers of AI.” But he now disagrees with his fellow computer pioneers about the best way forward. He recently discussed his vision for the future of artificial intelligence with CBS News’ Brook Silva-Braga at Meta’s offices in Menlo Park, California.
Stanford Adjunct Professor Pedram Mokrian reveals why AI has become such a high priority and how business leaders can think about developing and adopting AI solutions. He provides an overview of the key AI terms, trends, and concepts that inform business strategy. You Will Learn:
https://online.stanford.edu/courses/xdgt224-building-ai-enabled-organization
This video is the culmination of documentaries that cover the history and origins of computing-based artificial intelligence.
00:00 Intro
0:44 The Thinking Machine
52:22 In Their Own Worlds (Claude Shannon)
59:26 The Thinking Machines
1:13:47 The Machine That Changed The World
2:07:42 John McCarthy Interview
Lately there’s been an explosion in news around AI, with some new groundbreaking revelation every other day. With chatbots like ChatGPT and image generators like Midjourney and DALL-E, the landscape, especially for content creation, has irrevocably changed. There’s a LOT of angles to this topic and no end to the hot takes. So I decided to take this topic on the best I could. It almost broke me.
What is Generative AI and how does it work? What are common applications for Generative AI? Watch this video to learn all about Generative AI, including common applications, model types, and the fundamentals for how to use it.
How are technologies like ChatGPT created? And what does the future hold for AI language models?
This talk was filmed at the Royal Institution on 29th September 2023, in collaboration with The Alan Turing Institute.
Generative AI refers to a type of artificial intelligence that involves creating new and original data or content. Unlike traditional AI models that rely on large datasets and algorithms to classify or predict outcomes, generative AI models are designed to learn the underlying patterns and structure of the data and generate novel outputs that mimic human creativity.
ChatGPT is perhaps the most well-known example, but the field is far larger and more varied than text generation. Other applications of generative AI include image and video synthesis, speech generation, music composition, and virtual reality.
In this lecture, Mirella Lapata will present an overview of this exciting—sometimes controversial—and rapidly evolving field.
Mirella Lapata is professor of natural language processing in the School of Informatics at the University of Edinburgh. Her research focuses on getting computers to understand, reason with, and generate natural language. She is the first recipient (2009) of the British Computer Society and Information Retrieval Specialist Group (BCS/IRSG) Karen Sparck Jones award and a Fellow of the Royal Society of Edinburgh, the ACL, and Academia Europaea.
00:00 Intro
2:38 Generative AI isn’t new – so what’s changed?
8:43 How did we get to ChatGPT?
12:38 How are Large Language Models created?
22:48 How good can a LLM become?
26:57 Unexpected effects of scaling up LLMs
28:05 How can ChatGPT meet the needs of humans?
32:30 Chat GPT demo
38:07 Are Language Models always right or fair?
40:21 The impact of LLMs on society
42:54 Is AI going to kill us all?
Fei-Fei Li and Justin Johnson are pioneers in AI. While the world has only recently witnessed a surge in consumer AI, our guests have long been laying the groundwork for innovations that are transforming industries today.
In this episode, a16z General Partner Martin Casado joins Fei-Fei and Justin to explore the journey from early AI winters to the rise of deep learning and the rapid expansion of multimodal AI. From foundational advancements like ImageNet to the cutting-edge realm of spatial intelligence, Fei-Fei and Justin share the breakthroughs that have shaped the AI landscape and reveal what’s next for innovation at World Labs.
If you’re curious about how AI is evolving beyond language models and into a new realm of 3D, generative worlds, this episode is a must-listen.
Timestamps:
00:00 – Spatial Intelligence: A New Frontier
01:38 – Scaling AI: The Impact of ImageNet on Computer Vision
06:56 – The Role of Compute
09:16 – Data as the Key Driver
17:01 – Defining AI’s Ultimate Goal
18:58 – What is Spatial Intelligence? Unlocking 3D Understanding in AI
26:35 – Comparing Models: Spatial Intelligence vs. Language-Based AI
29:41 – 1D vs. 3D
32:39 – Building Immersive Worlds with Spatial Intelligence
35:11 – From Static Scenes to Dynamic Worlds
37:42 – The Future of VR and AR
40:42 – Creating Deep Tech Platforms
44:26 – Building a World-Class Team
45:54 – Measuring Success: Milestones in Spatial Intelligence
From January 2019, Scott Pelley’s interview with “the oracle of AI,” Kai-Fu Lee. From this past April, Pelley’s report on Google’s AI efforts. And from this past March, Lesley Stahl’s story on chatbots like ChatGPT and a world of unknowns.
Nathan hosts Professor Michael Levin and Staff Scientist Dr.Leo Pio Lopez from Tufts University in this episode of The Cognitive Revolution. They discuss their groundbreaking paper that combines biological datasets into a unified network model of disease using advanced embedding techniques. The conversation covers the technical details of their work, including a predicted link between GABA and melanoma, and explores broader topics in AI for biology. From multi-scale intelligence in biological systems to the future of human enhancement and digital life, this thought-provoking episode reminds us of the rapidly approaching future and the work needed to prepare for it.
Links to the papers discussed in the episode:
1) Universal Multilayer Network Embedding Reveals a Causal Link Between GABA Neurotransmitter and Cancer :https://osf.io/preprints/osf/d78wb
Artificial intelligence (AI) technology is developing at high speed, with big players like Google and ChatGPT-maker OpenAI transforming modern life.
However, some experts fear AI could be used for malicious purposes.
On this week’s AI Decoded, tech writer Parmy Olson and psychologist Gary Marcus discuss the implications of consolidated power in AI development.
