Competing and innovating in the fast moving SOTA end of the llm space requires a ruthless disregard for copyright, IP, bureaucracies, formalities, risk assurances and other slowdowns. It requires a risk tolerant, quick and large flowing investment of capital. It requires a scoped focus that is pragmatic and sharp about key concerns, and efficiently dismissive of meaningless details.
Europe can provide none of this. They will never be at the frontier of AI tech, for the same reason they were never at the frontier of any tech.
Sounds very interesting - I've been using just & docker (-compose) to manage my monorepo projects after a short frustrating stint with moon&proto. I like the simplicity of just, but onboarding can still be cumbersome, especially across platforms.
How do we know this is even what really happened?
There was a big wave of complaints on Reddit about Claude's output quality, and reports of subscription cancellations piled up.
Many people suspect some form of load optimization and/or quantized models, or other cost-optimization strategies that were applied as the cause for degradation in intelligence.
Seems like the complaints became loud enough for Anthropic to bother looking into it. But with zero transparency, zero additional info around the issue, it's hard to trust Anthropic not to continue to silently optimize for cost.
Why pay $200 a month if your "productivity boost" can randomly turn into lobotomized output overnight?
Anybody remember active learning? I'm old, and ML was much different back then, but this reminds me of grueling annotation work I had to do.
On a different note: is it just me or are some parts of this article oddly written? The sentence structure and phrasing read as confusing - which I find ironic, given the context.
The paper's core idea isn’t that all cells that use mitochondria need sleep, but rather:
> In a specific subset of sleep-inducing neurons, mitochondrial electron leak builds up when energy is available but underused during neuronal inactivity. That mismatch acts as a sleep signal.
I'd be interested to see, what results one would get, using that prompt with other models. Is there much more to ChatGPT Study Mode than a specific system prompt? Although I am not a student, I have used similar prompts to dive into topics I wish to learn, with I feel, positive results indeed. I shall give this a go with a few models.
The "web" is already just business infrastructure.
It already was, much prior to AI.
I would challenge the assumption that there is anything worth saving.
Behavioural patterns are heavily influenced by hormonal balance and as such, success-rates of different self-help strategies (diets, fasting, resistance and/or endurance training) are highly individual. This also extends to addictive behaviours.
"Hormon-typical" individuals have an easier time shaping their behavior because they don't face imbalances that complicate adherence. For them, sticking to a program is trivial. Combine that with lack of reflection, and many of these individuals delude themselves into thinking their success of following simple programs (which are simple in design, and only difficult in adherence) is somehow an accomplishment worthy of note. Low-empathy individuals, in particular, often interpret this as evidence of their own superiority, while dismissing others as mediocre.
So you see such comments a lot, because many people are "hormon-typical" and also low empathy. See any discussion about diet, fitness, Ozempic, etc.
How much of your time do you spend in writing for your blog? Do you do this full time or is it more of a side gig?
Your shout that "more people should do this" is resonating with me - I have some interest in similar short form posts covering various topics of interest (even if only for my own reference), but I am not sure if I can manage this on the side.
I'm curious about the time required for this volume of content output. Do you use AI to help with writing?
>Some of these students are dishonest. Many aren't. Many genuinely believe the work they submit is their own, that they really did do the work, and that they're learning the languages. It isn't, they didn't, and they aren't.
People are quite poor at this kind of attribution, especially when they're already cognitively overloaded. They forget sources. They mistake others' ideas for their own.
This attitude is common not only among students, in my experience many people behave this way.
Qualify it to software, rather than all tech, if you will.