@EthanEvansVP I think everyone hates that book, but it's also a great book that everyone should read
I once gave it at a company white-elephant, the recipient was very disappointed
Like many VCs, I really do believe Anthropic and OpenAI are the last startups.
There is no point to building anything else.
Everything has been solved or will be shortly.
At @zerg_ai we are constantly thinking about how software/technology will change with the different speed limits that govern current capabilities, for example:
- token speed
- context size
A short essay on the subject of the latter -
1/ ๐ง A 1M token context window changed what an agent could do in one call.
When a 1B token window arrives at scale, it will change what an agent can hold in its head.
It is painful to see how little attention this is getting - this is really awesome - have yet to see "world model" models actually show user/environment interactions like this - looks like you're utilizing an underlying deterministic engine with a top level video-gen model? Have always thought this was the golden path since GameGAN / GANCraft - equivalent of neuro-symbolic program synthesis for world modeling.
Very cool work
Most AI coding agents write code by retrying โ same broken approach, slightly rephrased.
A new paper from CMU, U Washington, and Arm asked the obvious question: What if the agent actually *remembered* what went wrong?
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