ashdksnndck

If I have a really straightforward question and I want a fast answer I’ll sometimes Google search for the AI overview. But it’s so unreliable. I use opus 5.5 for any question that Google could plausibly screw up. This is a huge product failure on Google’s part, IMO. I’m a $20/paid user for both Gemini and Claude. It’s nuts that with Google’s massive head-start in AI (and apparently they still are capable of making a frontier model), they somehow deliver such a crappy version of AI by default in their flagship product. Google is probably in some part responsible for the public’s distaste for AI.

Easy way to tell will be to wait and see if it gets fixed now that there is attention on the topic.

> if Anthropic models run in a Google cage, does that not also mean Google can distill Anthropic models even easier (both fast and unseen)?

Anthropic is indeed trusting Google and other companies they rent compute from. Distilling or stealing the weights would be a contract violation, and would wreck other business relationships. I would be less worried about Google doing this, and more concerned if there is some sketchy neocloud in a van offering suspiciously low pricing.

They’re giving 0% interest, which is a discount. It’s rational to take that instead of paying cash.

It makes sense to use an LLM to write the queries when exploring data, but if you are building a dashboard that’s going to be used repeatedly, you should save the queries so they can be validated and improved over time. The LLM shouldn’t be rewriting a new query every time you open the dashboard.

Interesting mindset.

You want to drive across town. You, only willing to deal in certainties, must decide ahead of time whether you will get in a crash. If you determine won’t get in a crash, you make the drive, pedal to the metal. If you determine you would crash, you stay home.

Me, willing to deal in probabilities, make the drive at the speed I feel reasonable and wear a seatbelt.

I don’t believe there is any fundamental reason LLMs can’t do this task, and the base models are probably already capable of it. RL to elicit the right behavior just hasn’t been done yet. Coding got solved first because it was cheaper and easier to get the necessary data for RL environments, which made it the natural first market opportunity. Solving white collar communication will require more resources to collect the data and build the environments, but the labs now have more resources and are working on it.

I want to believe reasons why this won’t work, but it feels like cope. It would be smart to be prepared for the world where knowledge workers get replaced by AI and also prepared for the world where AI is a bubble that pops.

The goalposts on what neural nets can possibly do have already moved past chess, go, protein folding, coding, poker, math, the Turing test…

Deceitful vs delusional or incompetent matters for your legal defense, your parole hearing etc

Was anyone confused by the title and thought we are exporting more gold in volume or weight than other products? It seems obvious that gold must be winning on value.

They still had to engineer the demo unit.

I demand a refund!

So if you knew in advance about the timing of both the tech bubble and the real estate bubble, you could have made a lot of money trading on that?

The input is unlimited size and the algorithm is achieving a speedup with constant size code.