0xpgm

It's likely the elected officials know nothing about AI the technology.

Depends on who has their ears in terms creating policies around technology.

Is that before or after the OpenAI and Anthropic pay off all the people and companies who's copyrights were violated when they used their works for free to train their models?

At least DeepSeek freely gives back the benefits.

Weird, isn't it? Microsoft owns all of LinkedIn, Github and NPM.

All three either have security or stability issues, which seems to get worse, not better, as microsoft goes more into AI. Where is the AI productivity (10x by some accounts!) within the company going to?

I use vanilla emacs and compile from source straight from master at whatever commit it happens to be in when I decide to do it.

Only once was there a noticeable breakage when a command like `git log` in the terminal would spit out all its output instead of displaying one screenful at a time. I'd expect someone following stable releases wouldn't experience any breakages.

From the article

> Matz has said as much. He’s described Ruby’s design as starting from a simple Lisp, stripping out macros and s-expressions, then adding an object system, blocks, and Smalltalk-style methods. The features most Rubyists fall in love with aren’t the object-oriented ones. They’re the functional ones, dressed in friendlier clothes.

There are some attempts at this problem, like Bittensor, Akash Network etc

If I remember correctly, the original GPT was considered too dangerous to release to the wild.

With hindsight, does that hold? If not, then how would we know a model is truly dangerous to release?

Hypothetically if LLMs were possible in the early 90s, what would the software ecosystem look like today?

Would it be 80s technology everywhere but widely deployed? Or would things have advanced further - better compilers, more ergonomic languages, better platforms etc? I don't know. But I suspect we'd still have needed people studying computer science to advance the state of the art.

Now looking forward 30-40 years from now, will everything still run on 2020s technologies?

Don't tell me were going to rediscover progressive enhancement all over again after more than a decade. Back when we used to actually care about the end user whether you were programming frontend or backend.

Too much VC money and big tech influence in the JS ecosystem made the web worse in some ways.

The best outcome of the AI hype for was to be the investment into next generation nuclear power plants, ushering the world into a post energy scarcity era.

Maybe we'll get there, maybe not. These days I only hear of datacenter investments.

These became popular after Moore's law made it possible many years after C/Unix had become the standard.

And they became just good enough that more people didn't go into Lisp/Smalltalk instead.

I highly respect the Ken Thompson and the rest of the old UNIX hands, but wouldn't they admit that the real world is messy and the best solutions in isolation don't always win?

Their creation C and UNIX won over the more advanced LISP and Smalltalk systems because they were simpler to implement. Even their own more advanced Plan 9 based OSs could not displace the more widespread unix-like systems.

It seems distribution and 'good enough' to rely on always wins. IMO, dynamic languages like Perl, Python, Ruby, JavaScript, PHP and the heavily marketed Java provided good enough high level facilities that have prevented people from reaching for Lisp and Smalltalk.

Looking at it through this lens, perhaps C++ was the vehicle for strapping some high level facilities on a widely adopted low level performant language that made it just good enough of a technology for wide adoption.

I'd also prefer journalists not outsource their writing to AI and doctors not outsource their diagnosis to AI etc etc

While it is human nature to minimize energy expended on doing things, progress has always come from the minority who prioritize disciplined thinking and action.

While minimizing energy spent worked well in historic periods where survival was hard, in this era of abundance and a complex, interconnected and fragile civilization, the same instinct becomes harmful.

> Outsourcing the work deprives you of who you become by writing it.

Just because AI can do something that resembles work should not mean outsourcing work to it. Mathematicians should not outsource their work to AI just like programmers should not outsource programming to AI.

Humans working with AIs in a tight loop means intellectual work becomes more high-level and creative, but a human should always own the work, validate it and stake their reputation to it. Simply ban any humans who produce low quality work using AI.

I'm curious, what would you say is DeepSeek's core competency?

I can't say what they should or should not be doing.

Generally, it is conspicuous how American companies are absent when it comes to state of the art open models. Meta tried for some time but it seems they've given up.

Perhaps, the issue is that the pace at which they release open models compared to their closed ones, shows that they are more committed on the closed ones and are not interested in advancing the state of the art of open models.

If I may guess, this is for a web3 internship?

It would depend on the complexity of the challenge. Knowing that a knowledgeable human took the time to verify the project/exercise gives a learner confidence that they are in the right track, not going down a path of hallucinations

Long tail effects of major events cannot be wished away

Still more to come I think. Until all the major AI companies IPO starting this year.

You'd think all these executives making investments into Agentic coding would throw money at something like Codecrafters so that their engineers ramp up their design and architecture skills.

> They (we) have to believe human brains still have value and find a way out; for otherwise there'd be no point to try anymore.

Are we already questioning the value of a human brain because of Large Language Models? Glorified search over a vector space? This is actual psychosis

It is said that these agents make one 100x more productive by some accounts. Microsoft is big on AI agents.

If these claims were true, why don't they point the agents at the numerous stability and security issues they have across their various platforms?

This is 2011 though, a lot has changed since then. I doubt Facebook/Meta, for instance, is still as flat as it was then having read some ex-employee accounts

There's a lot of deception going on with job numbers. Everyone knows there was a hiring spree during the pandemic and companies have been gradually shedding off excess weight since then. AI of course is just another excuse to shed more numbers.

I'd prefer it if people looking at hiring numbers would compare it with the pre-pandemic levels.

Things like this make me realize the software engineering 'industry' is not a real industry.

There are people who write important software that the world runs on, but they do it outside the 'industry'.

A real industry should be responsive to events of nature, or at least the market, not vibes.

> Uploading costs you nothing, and it can help the poor.

Could you expound more on this? Are you suggesting that less energy use in data centers would help the world's poor?

We keep seeing things like cryptic error messages shown to end users simply because of the disconnect between the programmer and the end user.

If the programmer gets to intimately understand the user's experience software would be easier to use. That's why I support the idea of engineers taking support calls on rotation to understand the user.

Both can be true at the same time, a product manager who retains the big picture of the business and product, and engineers who understand tiny but important details of how the product is being used.

If there were indeed perfect product managers, there would no need for product support.