Recent submissions

Comment · 9 months ago
Turkish TV series have been operating on this exact "second screen" logic for decades. They are massive global exports specifically because their 140-minute episodes rely heavily on meaningful stares, flashbacks, and circular dialogue.

They are designed for people ironing or cooking; you can leave the room for twenty minutes and miss absolutely nothing.

Personally, I can't bear them, the constant spoon-feeding is torture if you are actually paying attention, but Netflix is effectively just adopting this proven, low-attention retention strategy.

Comment · 1 year ago
Unclear if this is actually intended or just a temporary malfunction.

It feels like they might be pushing users to the Mac app, but there’s no official communication about it yet.

That’s why I posted it here on HN, hoping someone knows more.

Comment · 1 year ago
Isn’t giving LLMs “IQ scores” a category error?

Human IQ is norm-referenced psychometrics under embodied noise. Calling both “IQ” isn’t harmless, it invites bad policy and building decisions on a false equivalence. Don’t promote it.

Comment · 2 years ago
> we are inspired by the recent advancements in reinforcement learning (e.g., o1)

It is interesting to see what the future will bring when models incorporate chain of thought approaches and whether o1 will get outperformed by open source models.

Comment · 2 years ago
Me too. I use now https://fireworks.ai/ for vision models to test.
Comment · 2 years ago
It is strange that this model is not available on Together.ai to try it out after reading the blog artcile.
Comment · 2 years ago
Some currencies use more than 2 decimal places. For instance, the currencies of Algeria, Bahrain, Iraq, Jordan, Kuwait, Libya, and Tunisia are subdivided into 3 decimals.
Comment · 2 years ago
There is a logical error in this statement:

"governments and corporations silencing dissidents has done far far more harm to humanity than people losing their accounts"

People can not loose their accounts, because they are governed which makes silencing possible.

Comment · 2 years ago
Comment · 2 years ago
Last week, chatgpt literally generated a pptx file that I have downloaded, with the content that I asked for.
Comment · 2 years ago
This article and many people attempting to analyze this topic (and many others) are missing a key element: "incentives"!

Many developers are more passionate about technology itself – coding, solving complex technical problems, and creating efficient solutions. Their formal rewards (like promotions, bonuses, and recognition) are often tied to technical achievements. If a developer spends 40 hours on customer research, this effort might not be as formally recognized or rewarded as much as a technical achievement like developing a new authentication solution that benefits the entire team.

Shifting this dynamic is not just about encouraging developers to spend more time on product management. It requires a systemic change in how organizations value and reward.

Changing the incentive structure to be more user-centric and less technically focused would significantly impact middle and upper management roles. A shift would challenge the very foundations of their roles and responsibilities, potentially leading to a loss of control and influence.

It's likely that such changes would face subtle yet strong resistance from middle and upper management. These individuals often have significant political power within an organization and a vested interest.

Comment · 3 years ago
I have mixed thoughts about this approach.

Unification should mean creating a single interface that seamlessly interacts with multiple underlying services without needing custom adaptations for each case.

The issue with allowing for customization is that it leads to fragmentation. This defeats the purpose of having a unified API in the first place.

I'm not sure whether the convenience of unifying leftover common functionalities like authentication outweighs the complexity and reliance introduced by adding another layer to the tech stack.

Comment · 3 years ago
The expected pricing is very strange:

Regular Twitch Neurons (RTN) - running wherever there's capacity at $0.01 / 1k neurons

Fast Twitch Neurons (FTN) - running at nearest user location at $0.125 / 1k neurons

Neurons are a way to measure AI output that always scales down to zero. To give you a sense of what you can accomplish with a thousand neurons, you can: generate 130 LLM responses, 830 image classifications, or 1,250 embeddings.

Who came up with this? This is ridiculous. I understand the underlying issues but would still prefer a metric like seconds of utilization multiplied by the size of worker.

Besides this, the expected pricing doesn't talk about the expected pricing but just the pricing model. Have the feeling that this is not going to be competitive to platforms like Vast.ai

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