What went wrong and how to prevent this from happening again.

We recently stumbled across the first ever Hacker News thread discussing Attention Is All You Need, the landmark paper that describes the transformer architecture. The work had come out in the summer of 2017, but it took a while for the wider AI community to begin to grasp its significance and build on it. 

Most commenters at the time expressed interest or admiration. Some didn’t understand it. Others thought that the paper would probably be out of date in a few months. And one person asked what it could do for capsule networks.

But whatever happened to capsule networks?

Guide to AI is an editorialized newsletter covering the key developments in AI policy, research, industry, and startups over the last month.

Produced by Air Street Capital.

If foundation model economics is alchemy, what does that mean for hardware?

Read more at press.airstreet.com

Revisiting our work on European readiness.

It’s been close to six months since we published our report covering the challenges early-stage defense companies face in Europe. Since then, we’ve seen a rush of defense-related announcements from European governments, speculation about the future of US support for the Ukrainian war effort, and the Russian military continuing to step up its offensive.

Given the pace of developments, we’re re-examining our initial work and assessing what’s changed, what hasn’t, some points we didn’t evaluate last time, and where we go from here.

Yesterday, I was the opening act at the MIT Tech Review EmTech Digital conference, where I spoke about how easy it is to miss step changes in AI progress among the day-to-day swirl.

Guide to AI is an editorialized newsletter covering the key developments in AI policy, research, industry, and startups over the last month.

Produced by Air Street Capital.

Profluent releases the world’s first open source AI-generated gene editor.

You can read more in the New York Times: https://www.nytimes.com/2024/04/22/technology/generative-ai-gene-editing-crispr.html

We dive into data acquisitions strategies for AI-first start-ups, including scraping, synthetic data, annotation, labelling, simulation, data marketplaces, data sharing, gamification and more, with a focus on generative ai and deep learning.

In this piece we dive into why the analogy of "data is the new oil" is misleading. 

While it’s easy to brush this off, language matters, and the forms of short-hand we use have an outsized impact on how we perceive the world. 

This is only heightened when we approach the new and the unfamiliar. The number of AI-related analogies has exploded considerably in the past few years. At the same time, advances in capabilities have created a new generation of AI-first companies that are fighting to position themselves in emerging markets. 

Both these trends shed some light on the promise and perils of analogies and provide lessons for policymakers and entrepreneurs alike.