I call BS. It’s probably a white label around existing Broadcom IP, impossible to go from zero to this kind of chip in nine months. I doubt OpenAI had any significant contribution.
My current position is more on the operational side and AI allowed me to create a pretty significant software system for our technical ops, that the wider org liked and given me the resources to recruit flesh-made engineers to support.
AI has allowed me to keep shipping features and system even when holding a normally managerial position, so if anything it preserved some of my coding skills. I'd not have seen any code otherwise (writing code is a huge time sink compared to managing things around an org).
I pity those who need to contend with that as ICs, though.
The way forward is minimalistic smart hardware, like Meta's Raybans, until battery, optics and compute allow us truly miniaturized AR heasets. For now the price is too high and the utility too narrow to matter.
Environmental movements had a huge impact on public awareness and climate change mitigation. It sure didn’t come from the government themselves. We take many everyday steps to reduce our environmental impact, from energy to transportation to building to recycling. It’s all happening to one degree or another pretty much everywhere.
People are much better at saying what they don’t want rather than thinking about what they do. It’s more effective to throw everything in using LLMs, then using human judgment to sculpt away.
When the very first ChatGPT transformed a simple C "hello world" into Python. I knew it's special. I'm a very big supporter ever since, including some worried moments of pondering about what our future would look like and what's the meaning of a having a profession - especially software which defined my life from childhood - for my kids.
I'm now very good with LLMs as a user and at the system/product level but I understand it's not a simple story of replacing people. They're exponentially better than us at some things, and allow me to create things professionally which I couldn't do with an entire team of experts, but the bullshit compounds fast.
Out of laziness I several times asked Claude and ChatGPT each some torque figures and other simple, hard data related to my dirt bike. They often got it completely wrong, but full of confidence every time. I never trust LLMs with hard data, unless you RAG the PDF into the context and even then it's sketchy.
Yea, I’m sure the personal plans are subsidized. I have $200 Claude Max at home and straight API pricing at work and equivalent work would easily cost me 5x if not more on the API.
Bigger, because no one expects beauty from Fiat. That said, the Multipla was a bold and brilliant car. This one is only bold in the sense that “I can’t believe Ferrari allowed that to happen”. It’s kind of the Balenciaga of cars: will rich people buy just about anything with the right logo on?
Can't avoid gloating over this one. Just like the Palestinian identity was created and weaponized against Israel by the Arab world, now Canadians will get a taste of their own medicine courtesy of the Trump admin.
The problem is that technical debt is compounding. Bad LLM architectural and implementation decisions just blend in to the background and you build layer upon layer of a mess. At some point it becomes difficult and expensive (token wise) to maintain this code, even for an agent.
I mitigate this by few things:
1. Checkpoints every few days to thoroughly review and flag issues. Asking the LLM to impersonate (Linus Torvalds is my favorite) yields different results.
2. Frequent refactors. LLMs don't get discouraged from throwing things out like humans do. So I ask for a refactor when enough stuff accumulates.
3. Use verbose, typed languages. C# on the backend, TypeScript on the frontend.
Does it produce quality code? Locally yes, architecturally I don't know - it works so far, I guess. Anyway, my alternative is not to make this software I'm writing better but not making it at all for the lack of time, so even if it's subpar it still brings business value.
Scientists and engineers also invented Zyklon-B gas and built the crematoriums in the concentration camps. Don’t underestimate what scientists and engineers can do to Jews.
It's kind of a learning JIT. It's no use to go through and memorize something you don't need in the short term. It's hard to memorize well and by the time you need to draw on the knowledge it's already hazy.
This is why you can think of such documentation more as a reference manual and not just plain documentation.
In any case, AI is great for traversing a codebase and producing at least a draft of such documentation.
In terms of runtime performance of applications, AI is a net win. You can easily remove abstractions like Electron, React, various libraries. Just let the AI write more code. You can even do the unthinkable and write desktop native again.