The world of artificial intelligence and machine learning moves very fast. So fast, in fact, that it’s remarkable to think that it was only a decade ago when the AlexNet model dominated the ImageNet competition and kicked off the process that made deep learning a bona fide technology movement. Today, after years of headlines about game-playing, we see ever-increasing innovation that applies to the real world.
In the last couple of years alone, AI/ML models like GPT-3 and AlphaFold delivered capabilities that catalyzed new products and companies, and that stretched our understanding of what computers can do.
With that in mind, we thought we’d revisit our AI/ML coverage in Future over the first half of the year, as well as catch you up on some — but certainly not all — of the major industry developments during that time. As you’ll see, some combination of large language models, generative models, and foundation models are a major source of attention, and we’re just skimming the surface in terms of understanding what they can do and how the world outside of large research labs can utilize their power.
The Future focus: How to take advantage of AI/ML advances
How to Use Massive AI Models (Like GPT-3) in Your Startup by Elliot Turner / Hyperia
AlphaFold, GPT-3 and How to Augment Intelligence with AI by Niko Grupen / Cornell
AlphaFold, GPT-3 and How to Augment Intelligence with AI (Pt. 2) by Niko Grupen / Cornell
Data50: The World’s Top Data Startups by Jennifer Li, Sarah Wang, and Jamie Sullivan / a16z
Emerging Architectures for Modern Data Infrastructure by Matt Bornstein, Jennifer Li, and Martin Casado / a16z
A Decade of Deep Learning: How the AI Startup Experience Has Evolved with Richard Socher (Q&A) / you.com
7 Techniques for Building Reliable AI Models by Beena Ammanath (book excerpt) /Deloitte
The Two Things We’ll Need for the Next AlphaFold with Daphne Koller (Q&A) / Insitro
Industry focus: Images, words, and more coding
Competitive Programming with AlphaCode / Deepmind
DALL-E 2 / OpenAI
Imagen: Text-to-Image Diffusion Models / Google Research
These types of advances, and the increased understanding of how to utilize them, are why we’re dedicated to stepping up our coverage of AI/ML and, in particular, how we’ll see it applied in real-world settings over the next few years. From biotechnology to television, we’re poised for a serious reimagining of what’s possible and how software can help humans deliver on their wildest ideas. If you’re working on something exciting and novel in the AI/ML space and want to share your thoughts on where we’re headed, please send us a pitch.
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