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Grok3 Launch [video]

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Re: Grok3 Launch [video]

#344
post #332
post #166

Earlier quoted context omitted.

Because he brought coders to a financial audit. Wrong tools.

“Figures don’t lie, but liars can figure”. You can easily get drowned by a see of numbers and get confused and gaslighted, unless you don’t make sure all data is available and computable. Not sure how this release, which impressive by all means transformed into an attack on DOGE which is the exact approach startups are taking to disrupt an industry.

Because it's not their data.

How much disruption started with massive failures?

You don't start with a live system or did SpaceX put astronauts in therir first rockets?

Re: Grok3 Launch [video]

#345

Off topic, but just in case: is there a good reference on how people actually use LLMs on a daily basis ? All my attempts so far have been pretty underwhelming: * when I use chatbots as search engines, I'm very quickly disappointed by obvious hallucinations * I ended up disabling github copilot because it was just "auto-complete on steroids" at best, and "auto-complete on mushrooms" at worst * I rarely have use cases…

LLM are good at one thing, and totally by chance it is the thing they have been designed to be: be a word probability generator. If you can constrain your usage around that, they are great to use. But the people who think they can reason or know some kind of truth are delusional

Re: Grok3 Launch [video]

#346

Off topic, but just in case: is there a good reference on how people actually use LLMs on a daily basis ? All my attempts so far have been pretty underwhelming: * when I use chatbots as search engines, I'm very quickly disappointed by obvious hallucinations * I ended up disabling github copilot because it was just "auto-complete on steroids" at best, and "auto-complete on mushrooms" at worst * I rarely have use cases…

My biology professor provides basically zero feedback on his student's understanding of the material. There are very few practices questions to prepare for exams, which are worth 40% of your grade. I had an LLM write some python that extracts the relevant textbook chapters, which then I can feed into an LLM to generate practice questions. Then I can ask the LLM for feedback and whether or not I'm articulating the answers correctly.

Re: Grok3 Launch [video]

#347

Off topic, but just in case: is there a good reference on how people actually use LLMs on a daily basis ? All my attempts so far have been pretty underwhelming: * when I use chatbots as search engines, I'm very quickly disappointed by obvious hallucinations * I ended up disabling github copilot because it was just "auto-complete on steroids" at best, and "auto-complete on mushrooms" at worst * I rarely have use cases…

Cooking & Meal Planning:

- I have these three ingredients; recommend Italian main courses.

- What other ingredients pair well with this?

- How can I "level up" this dish if I want to impress?

- Can I substitute X for Y?

- Generate a family-friendly meal with lots of veggies using leftover roast chicken.

Re: Grok3 Launch [video]

#348

[flagged]

Look who builds it. Its not Musk. Its his money who bought smart people.

If he does to the USA Gov what he did to Twitter, he will destroy the brand, reduce the workforce by 80% and reduce the value by 80% too.

The issue with him is, tha tin Twitter, the affected people had money. A missed payment of USA can literaly kill people.

Re: Grok3 Launch [video]

#349
post #258

Earlier quoted context omitted.

There are two answers to this. Answer 1: Some people think that LLMs are a path to the singularity, a self-improving intelligent program that will vastly exceed human intelligence and will be able to increase its knowledge exponentially, quickly answering all answerable scientific questions. Answer 2: LLM companies need to keep the hype train rolling. I didn't watch the whole clip; I jumped around a bit, but I notice…

There's a more short-term goal for Grok, which is to replace what is left of the federal government with AI. That will significantly boost the money train, but is also a utopian (for some, dystopian for others) goal of replacing the expensive 'deep state' with a slim set of impartial algorithms.

LLMs don't seem to be very impartial so far. Quite the opposite in fact, they're entirely beholden to the prejudices of their trainers.
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