This is our first weekly post so the thoughts here are somewhat expanded, and there’s a lot to catch-up on…
A tech tsunami: The ChatGPT inspired rush to AI from late 2022 has triggered a surge of investment, research, software and hardware competition that this month has started to hit the mainstream. Much like a tsunami there ‘s a lot more to come, and it won ‘t stop for the foreseeable; Apple, Amazon, and Meta are just getting going, (these three alone spend more on R&D each year than all of the companies and the governments in France, UK, Italy, Spain and the Netherlands combined).
Attenuated progress for now: Like computing waves before it, AI is seeing high-end launches combined with smaller, faster, cheaper evolution at scale. But there is still hidden constraint… compute (a single factory in Taiwan makes all of the worlds AI chips). Think Nokias to iPhone 15s in 18 months, but being stuck on 1G networks and nowhere to charge your slab of titanium and glass. Sora and Gemini show that ‘laboratory ‘ models will become many times more powerful in the coming months, and Gemma demonstrates the efficiency curve, but the emergence of chips from the likes of Groq suggest the underlying compute problem can also be solved with AI-native hardware.
Outlook: As of this week, our timelines to AI systems that reach human equivalence (AGI) are shortening. Two recommendations continue to hold true…
- 80% of your AI time should be spent on experimenting with current state AI in its currently workable forms; combinations and novel uses will uncover many competitive advantages.
- 20% of your AI time should go to envisioning solutions that may seem near-impossible today, but could arrive much sooner than expected. Those who can capitalise quickly on step-changes will have an unprecedented strategic advantage.
Now over to Exo for a news roundup…