@brian_armstrong indeed frontier models seem to handle context rot on long running tasks much better now even with inter agent communication steering models for periods
building against anthropic and with anthropic at the same time feels like a fools errand
when the core product is general intelligence and the lab consumes the application side it feels like your startup can be consumed any moment.
and if alignment can be replicated at test time then the amortization costs and time to deployment of open weight models becomes EV- �� the cost benefit of each design is still up in the air as stronger models break previous assumptions
it’s said to build assuming the models will improve and labs will continue to consume the product side. if you don’t own the end rails that distributes trust then you’ll just be a temporary fde for the labs distributing intelligence
or as they say software is going to zero so you need to own how the trust is distributed
Introducing Inkling 2 Small. Scoring 31 on the AA Intelligence Index, it's a big jump over its predecessor.
Inkling 2 Small is available for fine-tuning and inference on Tinker today, with full weight release planned soon.
https://t.co/VR02tw73fJ
Top of the Democratic agenda on day 1 needs to be a pause on advanced AI development, regulation of this out of control industry, and a ban on artificial superintelligence.
@patrickc This is fine when the population isn’t subverted. It’s quite clear that foreign and domestic players are working to destroy democracy from within.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: https://t.co/bOWCcFhCVq
you can get far with prompt optimization. but i agree owning your intelligence (at least preparing for it as compute costs come down and open intelligence rises) will set companies apart.
Own your intelligence.
Anyone that opposes this has something to sell you (perhaps your own intelligence back to you.)
Local models need to continue proliferating. The “absolute unit” massive models may be out of reach for now locally, so your best option is to, indeed, keep your options open. Own your harness, data, connections, runtime: your agents. Embrace open source.
New in Claude for Legal: a gallery of ready-made artifacts for contract review, regulatory horizon scans, cite checks, and more.
Start from the built-in example, add your own documents and connectors, and share it with anyone across the business.
@garrytan@ycombinator i would also say direct messaging isn’t ideal for swarms on long running tasks but to test the limits of these systems on frontier models you need a lot of compute