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.
Prof. Alexander G. Ororbia is a researcher in the field of bio-inspired artificial intelligence, working on on mortal computation and neurobiologically-plausible learning algorithms. Ororbia takes us on a tour of brain-inspired AI, discussing how concepts like predictive coding, forward-only learning, and neural generative coding can lead to more efficient and adaptable AI systems.
He explores the how we might implement these bio-inspired approaches on neuromorphic hardware, and shares his vision for a future where AI systems are more closely aligned with biological intelligence.
TOC:
Foundations of Bio-Inspired AI [00:00:00] 1.1 Introduction to Bio-Inspired AI and Mortal Computation [00:04:50] 1.2 Principles of Mortal Computation and Biomimetic AI [00:17:41] 1.3 Markov Blankets and Free Energy Principle [00:24:38] 1.4 MILLS Framework and Biological Systems
Alternative Learning Paradigms [00:31:00] 2.1 Challenging Backpropagation: Overview of Alternatives [00:31:49] 2.2 Predictive Coding and Free Energy Principle [00:41:52] 2.3 Biologically Plausible Credit Assignment Methods [00:50:11] 2.4 Taxonomy of Bio-inspired Learning Algorithms
Advanced Bio-Inspired AI Implementations [00:59:30] 3.1 Forward-Only Learning and NGC Learn Implementation [01:03:25] 3.2 Stability-Plasticity Dilemma and Bio-Inspired Solutions [01:09:00] 3.3 Neuromorphic Hardware Landscape and Challenges [01:12:58] 3.4 Neural Generative Coding and Predictive Coding Advancements [01:20:36] 3.5 Latent Space Predictions in Forward-Only Learning
REFS: The Levin Lab https://drmichaellevin.org/
Mortal Computation: A Foundation for Biomimetic Intelligence https://arxiv.org/pdf/2311.09589
The Forward-Forward Algorithm: Some Preliminary Investigations https://arxiv.org/pdf/2212.13345
Good regulator https://en.wikipedia.org/wiki/Good_re…
The free-energy principle: a rough guide to the brain? https://www.fil.ion.ucl.ac.uk/~karl/T…
Hebbian theory https://en.wikipedia.org/wiki/Hebbian…
There’s Plenty of Room Right Here https://www.ncbi.nlm.nih.gov/pmc/arti…
Active Inference: The Free Energy Principle in Mind, Brain, and Behavior https://direct.mit.edu/books/oa-monog…
Brain-Inspired Machine Intelligence: A Survey of Neurobiologically-Plausible Credit Assignment https://arxiv.org/pdf/2312.09257
Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects https://www.nature.com/articles/nn019…
NeuroEvolution of Augmenting Topologies (NEAT) https://nn.cs.utexas.edu/downloads/pa…
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods https://arxiv.org/pdf/2205.11508
A Path Towards Autonomous Machine Intelligence (Yann LeCun) https://openreview.net/pdf?id=BZ5a1r-…
Test-Time Model Adaptation with Only Forward Passes https://arxiv.org/pdf/2404.01650v2
Sep 19, 2024 The Inaugural lecture for the new Living Well With Technology series from the Digital Futures Institute at King’s College London.
The public lecture AI: The means to an end or a means to the end? was delivered by actor, author, broadcaster and comedian Stephen Fry.
The Institute’s new Thought-Leadership Series - Living Well With Technology is an events programme and associated book series convening thought leaders from across the tech, health, policy, business, education and creative sectors to collaborate on the creation of a better digital future.
Artificial Intelligence in Healthcare is revolutionizing the medical industry by providing a helping hand. This Edureka session will help you understand the positive impact of Artificial Intelligence in the healthcare domain along with practical implementation in Python. The following topics are covered in this session:
Apr 18, 2020 #Ranga_Yogeshwar Artificial intelligence (AI) is changing our lives. It touches on all aspects of society - private life, business, security -- including in the spread of fake news and the challenges posed by the advent of autonomous weapons.
This documentary looks at the rapid change digitalization is causing as it unfolds. In particular, breakthroughs in artificial intelligence are opening completely new horizons. In their film about AI, Tilman Wolff and Ranga Yogeshwar examine the role AI plays in the spread of fake news. They also consider a future with robots and the risks and ethical questions posed by the development of autonomous weapons. To address these issues, they travel the globe to speak with leading experts. AI can generate perfectly forged sound and videos, making it effective for purveying fake news. Discerning the truth from fiction will become increasingly difficult. Technology will streamline work, making some jobs surplus to requirements. Software will pilot self-driving cars and aerial drones. AI is rapidly opening up new vistas, but turning blind corners at speed can be risky. How sensible is this type of progress, and at which point should society step in and set limits to its development?
A documentary by Tilman Wolff und Ranga Yogeshwar
Large language models-- or LLMs --are a type of generative pretrained transformer (GPT) that can create human-like text and code. There's a lot of talk about GPTs and LLMs lately, but they've actually been around for years! In this video, Martin Keen briefly explains what a LLM is, how they relate to foundation models, and then covers how they work and how they can be used to address various business problems.
