I want more of these present memes please 🙏
Mastodon: @greg@clar.ke
I want more of these present memes please 🙏
The issue is that many YouTubers do no due diligence for the products they promote to their high trust audience.
What an I looking at here? What’s the white stuff? Snow?
I don’t think this guy is Satoshi but no Bitcoin wallets known to belong to Satoshi have been active since their initial transactions. I think it’s likely that the keys for those wallets have been lost. So I don’t think the inability to sign these messages proves that he’s not Satoshi, the fraud does though.
Or even 200% ¯\_(ツ)_/¯
Cheers, I can read and comprehend the original headline now. I’m Australian so English isn’t my first language, at least that’s my excuse.
Is there missing punctuation in that headline or am I an idiot?
Google is a publicly traded advertising company with quarterly goals and a track record of lying about their AI offerings. “Google” used to be synonymous with finding things, now “Google” is synonymous with enshittification. The only thing keeping Google’s search offerings relevant is monopolistic behavior and inertia.
OP can use a Cloudflare tunnel which would take care of caching and prevent any accidental DDoS attacks.
It’s scary that some people’s first instinct to get reliable information is to ask Facebook. But to be fair, government websites are usually difficult to get navigate and Google search is useless nowadays.
That’s my point, if the model returns a hallucinated source you can probably disregard it’s output. But if the model provides an accurate source you can verify it’s output. Depending on the information you’re researching, this approach can be much quicker than using Google. Out of interest, have you experienced source hallucinations on ChatGPT recently (last few weeks)? I have not experienced source hallucinations in a long time.
Generative AI is a tool, sometimes is useful, sometimes it’s not useful. If you want a recipe for pancakes you’ll get there a lot quicker using ChatGPT than using Google. It’s also worth noting that you can ask tools like ChatGPT for it’s references.
I know the difference. Neither OpenAI, Google, or Anthropic have admitted they can’t scale up their chat bots. That statement is not true.
That may have been true for the early LLM chatbots but not anymore. ChatGPT for instance, now writes code to answer logical questions. The o1 models have background token usage because each response is actually the result of multiple background LLM responses.
The title of the article is literally a lie which is easily fact checked. Follow the links to quotes in the article to see what the quoted individuals actually said about the topic.
No, a chat bot as it’s talked about here is not an LLM. This article is discussing limitations of LLM training data and inferring that chat bots can not scale as a result. There are many techniques that can be used to continue to improve chat bots.
I’m sorry if I’m coming across as condescending, that’s not my intent. It’s never been “as simple as just throwing more data and CPU at the problem”. There were algorithmic challenges for every LLM evolution. There are still lots of potential improvements using the existing training data. But even if there wasn’t, we’ll still see loads of improvements in chat bots because of other techniques.
Edit: typo
People that don’t understand those terms are using them interchangeably
Yes of course I’m asserting that. While the performance of LLMs may be plateauing, the cost, context window, and efficiency is still getting much better. When you chat with a modern chat bot it’s not just sending your input to an LLM like the first public version of ChatGPT. Nowadays a single chat bot response may require many LLM requests along with other techniques to mitigate the deficiencies of LLMs. Just ask the free version of ChatGPT a question that requires some calculation and you’ll have a better understanding of what’s going on and the direction of the industry.
Those bots are not going to be happy