“Oracle petitioned the court against the requirement, arguing that these financing costs would deter future investment in the state, while emphasizing its commitment to the project, […]. Regulators, on the other hand, remained firm in their stance, clarifying that existing customers should not subsidize data centers. This issue is not limited to Wisconsin: At least 24 US states have already approved special rates, minimum conditions, exit penalties, and collateral requirements for heavy electricity consumers.
I believe that living a happy life is a long term survival strategy. Producing offsprings is the other way. If we feel miserable, we want to cut our life short or it will be due to many problems, bad health included. Long term happiness is a very good measure of how good your life is going. So while we might not agree on whether we should optimize our lives for happiness, it's certainly an objective we should always consider. However, we should not confuse happiness with pleasure. One is meant for the long term, while the other is ephemeral.
I have a problem with the cost per task metrics of Artificial Analysis. We don’t know how they calculate it exactly. But recently, cost per task has become the most discussed topic. The logic is basically: if model A achieves 55% on benchmark X and model B 60%, but the cost per task of A is 50% cheaper, people would choose A instead of B.
But that implies that all output of the less intelligent model A is usable, perhaps only a bit worse than the output of B. But what if the output of A is unusable, or it can only deliver usable results in 1 out of 5 tries? In such cases, the user will have to rerun the task and it will very quickly double or triple the cost and makes the old average number misleading! I would argue the retry and flaky cost will be many times bigger than the average token cost and that is the true cost the users have to bear.
AI-Benchy [0] (admittedly a one man benchmark) shows a much different figure than the numbers of Artificial Analysis. Opus 4.8 cost per task according to AA is $1.80 and Kimi K3 is $0.94$. According to AI Benchy, however, the *cost per successful task* of Opus 4.8 is 10.7 cents vs 19.4 cents of K3. The number of correct tests and pass rate of Opus 4.8 is also higher than Kimi K3.
So on a cost-per-usable-result basis, Kimi K3 is actually pricier than Opus 4.8 — the opposite of what AA’s headline number suggests.
Thus, I don’t know if I can believe the numbers of AA or we need to track the cost ourselves.
In this book, Sanjoy Mahajan shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering. (Description courtesy of MIT Press.)
With these heatwaves, many cities in France, Italy and England are at times *hotter* than cities in the tropical SEA! No wonder the bananas are starting to fruit.
Nope! GPT just cheated (by search the web). If you changed the text, export as image, GPT 5.6 Sol will fail. I tested with other text and even with a hint of a hidden text underneath, GPT 5.6 Sol could not see it.
Extrapolating to other fields, we can say this development is the worst what one can do to mankind and society: pushing for AI but at the same time decimating the human capital that helped produce and understand it. What is the point of producing countless mathematical proofs or code that one cannot verify nor understand? It’s like having a machine to produce endless things that no one needs or will use. Just because the machine can bring profits for the (initial) investors?! That is the rottenest form of capitalism imaginable.
The last and most important moment was not clear at all. I wonder why they had to cut the video right there and not let it extinguish the fire and stand tall on the landing platform as SpaceX has done all the time. Even Blue Origin showed the final moment very clear with the explosive riveting.
It said “3D-looking Rubrik cube”. Maybe your cube looks different but I’m pretty sure for everyone else, the GPT result doesn’t look like a 3D-looking Rubrik cube.
And I wonder if somebody has tried with the available galactic data and see if the genetic programming can come up with a better formula than MOND or Einstein's general relativity.
For simple problems as Kepler's law, a quick detour on Desmos will show a perfect fit for power law instantly. In general, there are many important criteria for a better curve fitting (for ex. independent, normal distributed residuals), not just R, so I hope the author has/will incorporate them into the search to create a more robust result.
Medical and long-term care expenses outweighs by a large margin the loss of consumption or tax revenue for retirees, especially for a welfare state like Germany. Many studies in Germany have showed exactly this constellation of cost-benefit.
When people came to the country to work then retire somewhere else, isn’t it not a net benefit for Germany? Less burden on the social net, healthcare system etc.
While attribution is a strong weapon in fighting malicious software, persevering the ability to install and run anonymous software is essential to fight authoritarian regimes and corrupt systems. If we accept that only signed, permitted software can be installed and run on users’ phones, democracy and our freedom are doomed. Regardless if it is in the West or the East, or it’s against an AI overlord.
“Oracle petitioned the court against the requirement, arguing that these financing costs would deter future investment in the state, while emphasizing its commitment to the project, […]. Regulators, on the other hand, remained firm in their stance, clarifying that existing customers should not subsidize data centers. This issue is not limited to Wisconsin: At least 24 US states have already approved special rates, minimum conditions, exit penalties, and collateral requirements for heavy electricity consumers.