samayashar

Welltower and Palantir are doing an amazing job! A comparison with NVIDIA in terms of market cap per employee isn't realistic here, but perks to them for the utility that each employee is bringing to the table.

I've been actively using Docker for most of my projects over the past few years and I sincerely thank you for brainstorming and getting it out in the market.

The sole idea of containerising an application, its utils and dependencies all into one container is a real big deal in early 2010s. The product has been so visionary that it has been re-pivoted as secure sandboxes which is most needed right now. Kudos!

This scares me to be honest. We have an exponentially decaying graph if we compare resources on y v/s consumption on x. I don't know what the next 50 years are going to bring considering the total resources to use on Earth are an "infinite constant".

> The major providers are unprofitable after you add in the training and research costs and other overheads.

This is correct for now, but I recently read that 90% of Anthropic's code is written by Claude Code itself. So, if an AI is using its previous version to train the next version, we're not far from the day where these models will take up the decision making process too. For eg: Decisions API by OpenAI or Jev is based exactly on this. What if a model like Jev sits behind Opus 5.5 and guides it to take the next step? Wooh.

Probabilistic predictions right now are at 99% for frontier models. They will never be 100%, but if humans rate themselves 99.9% in decision making, that benchmark can be broken.

I see a lot of micro-chip designs that are so cool, but they just exist as a design in some software on our computers. If this printer can allow cheap and sustainable printing of chip designs, then the hardware field could take a very interesting turn!

Every few months, Mistral becomes active and drops a bombshell.

WHAT IS THIS

> That means tools should return structured data and tools should be discoverable by their documentation and description.

Treating MCP as a part of OpenAPI rather than a tool connector is a direction in which we're heading. It is important for the users to have the flexibility of deciding the model, work to be done and the tool call in one prompt. The framework sets up the configuration and gets the output.

The Sol series might be OpenAI's best release for everyday tasks. The model provides great all-round performance at a nominal cost.

I've been actively using it since the past couple of months and it has rarely disappointed me.

Really good to see AI being integrated in the government. One of the places where it's needed the most since there are so many individual websites and navigating across them can be tough.

The author is right to categorise AI as a good programmer, but not a complete coder. We can all agree that programming has become really fast since the release of GPT-5 series and Opus models because they're pretty good. Not only this, they've also changed the pace expectations across teams where a feature that should ideally be delivered within weeks, should now take days.

All this doesn't change the fact that software engineers are going nowhere because nobody trusts AI. If a model can escape highly secured sandboxes, then we're definitely not running these agents overnight on our systems. I am sure the next-gen of models will focus more on security and the trust factor will start developing, but that's a long way down the road.

People trust people, not systems.

As models get better, safe-and-secure sandboxes/environments are going to be the way forward. With the recent rise in cases where models can somehow gain access to the internet and blast past the sandbox, it's very important to have all the resources contained within the sandbox with no access to the outside world.

DSec is a good step in this direction!

This statement should be restricted to answers for provocative questions. If an LLM is being asked a question that goes against the guidelines, then "As a Language Model..." is a valid starting point. Rest, obviously we're aware that a software doesn't have the judgement that a human has.

I am unable to understand what happens if the watermarked output goes as input to another agent. Let's say we asked Claude a question and got a watermarked response. If we pick that response and append it to the question we're asking ChatGPT, then will it answer or refuse to do so?

If that's the case, then it's a brilliant strategy by the labs to cut down cross-AI usage and just stick to one model. But I'm pretty sure this won't be the case.