mmcnl

In practice you will hardly ever notice this. Especially not during normal use. Maybe only during videos.

OLED displays now are tandem OLED displays which stack multiple layers. This means you don't need to exponentially crank up the voltage to provide more brightness which also increases lengivity of the panel (and increases battery life).

In my experience AI widens the gap, not closes it. The best engineers are 10x more productive, the worst engineers maybe 2x.

Asking questions is not the same as doing work.

LLMs need deterministic verification to enable a quick and short feedback loop before they become really powerful. Software is uniquely positioned to provide this feedback loop. Much less in other industries.

Yeah, if you're wandering in random directions all day long (20 PRs a day is rarely working towards a clear goal) then you're not going to get far. Taking some time to figure out where you're headed is probably way more beneficial in the long term. And it's also something LLMs suck at, they interpolate extremely well but haven't got a clue what's next.

Maybe I'm too doomer, but if a large portion of the population becomes economically worthless, how can this not have a destructive effect on society? It would be easier for anyone with power if you wouldn't exist. How would that not lead to corrosion of basic human rights (or worse) and the spawn of a new permanent underclass which you cannot escape from? It sounds very dystopian but if AI is left unchecked this will happen imo.

It's only fair if 99% of revenue flows back to humanity. The models are worthless without its training data.

I think it's unsettling that a bunch of billionaires hold so much power. Does it really matter if 2 or 3 billionaires who are practically neighbors hold so much power? It's extremely concentrated with or without Meta joining the race.

This is nice in theory but in practice impossible.

I don't understand. Code doesn't capture the context in which decisions were taken: why is code the way it is? What is important? What is not? How can agents make correct decisions without knowing context that cannot be inferred from code?

Why are we not curing cancer? We should.

Yeah this is misleading cherrypicking. Also it's super slow. Not impressed with slow efficient chips. Anyone can make a chip efficient by reducing clock frequency and sacrificing performance in the process.

Easy, it's priced much lower in the US on purpose so that reviewers will directly compare it with the Neo to get more favorable reviews, while in fact it should be compared to the Air from a price perspective (and then it will lose on everything big time except the 120Hz display). It's all misleading marketing.

MacBooks simply have the best value proposition. Compared to the competition at similar price point they are much faster, have much better build quality, better displays, better battery life, less fan noise, etc. Also much higher resale value.

You're completely right. Power draw scales non-linearly with clock frequency. Therefore one can easily increase perf/W by lowering the clock frequency, at the expense of performance. This is not new information, this is basic physics. The Apple M-chips were not revolutionary because of their efficiency, but because they were (and still are) efficient AND fast. In fact the fastest consumer chips on the market.

So agreed, this is extremely misleading.

For me this metaphor only makes the original point more credible.

There are many math problems that are simply puzzles: intellectually interesting but nothing worth of value depends on it. To me it would be more impressive if we could define hard problems that need to be solved up front and see how the models deal with that.

The results OpenAI demonstrated are impressive, but it also looks like they threw a lot of compute at it just to get results. How many tokens did they waste on problems they couldn't solve? Applying inference infrastructure on a large number of math problems at scale we haven't seen before to me doesn't demonstrate an exponential curve in model abilities.

Sooo true, AI never asks questions. It just makes up requirements. I think it's because the models are trained on benchmarks where task completion is an important metric. But I'd rather have it not finish a task and specify why than make up stuff along the way.

I recognize this, LLMs never stop, they pursue the dead end at all costs.

The real value I think never really was the code, it was the learnings from the journey to get to the code. The struggle allowed for iterative discovery of the real requirements and technical challenges. With AI you skip that path and it looks like you've achieved your goal only on a superficial level.

I think this doesn't mean AI is useless (it's not), it's just that we have to think harder about the requirements and end-stage verification and have less trust in the process to result into valuable outcome.

Indeed. I wonder how much AI will do in industries with longer feedback loops that are much noisier. I think the field of software is a unique field in that sense.

I think other industries are late, but also will see less productivity gains. In software engineering agents have the benefit of very short feedback loops that provide extremely actionable insights which allows the agent to very quickly iterate towards the final solution. This is much less the case in other industries such as law and finance I think. The first pass of the agentic loop is usually something that barely works (you don't even get to see it with the latest models). If that first pass is the primary output in other fields with no tight feedback loops, then the productivity boost will be much lower than in software.

Plex has a great Tizen app. It just works on my TV same as Netflix.

Hardware revenue is 3x the services revenue, even with half the margins it still generates more profit than services. I get that Apple would like to increase service revenue but they are a hardware company at heart and their financial statements show it too

The battery life stinks, the build quality is subpar and the fan runs all the time. If you don't care about anything that makes the MacBook Pro a premium device, then sure you can be overpriced consumer-grade slop that has a slight edge in specs (except CPU). But it's a miserable trade-off.

This is just plain wrong. Apple generates most revenue and profits with hardware and it's not even close.

The world would be a better place without AI, OpenAI, Anthropic and all others. It only immerses the world into chaos, dystopia and increased inequality. So far nothing for the public good has come out of it.

The AI "market" is not a free market. It needs regulation.

Very normal in The Netherlands, was kinda surprised to learn it's not a thing in English speaking countries?

Not in some ways. The value of working code that meets the requirements and generates revenue is very high, it's a gift.