11–20 of 22 posts
Why would anybody trust this after they faked the last Gemini demo?
I simply don't believe the model is that good. Otherwise, maybe try to compete with OpenAI directley?
Why would anybody trust this after they faked the last Gemini demo?
The code changes are the most common tutorials you can find on the web. Adding a speed slider, the terrain tutorials are literary called "height maps" and focus on making it taller or flatter.
Why would anybody trust this after they faked the last Gemini demo?
Exactly. Give us access the model and let independant researchers test it. OpenAI did this with GPT4, opening access publicly and deeper access to researchers within and outside of Microsoft. I simply don't believe the model is that good. Otherwise, maybe try to compete with OpenAI directley?
But the input was still divisible into self-contained little bits -- so this is still somewhat different from dumping the full source code for a database engine into it, and having it answer questions about, say, where foreign key constraints are implemented -- or, more dramatically, how several different parts of the codebase work together to implement, say, transaction isolation levels.
Why would anybody trust this after they faked the last Gemini demo?
Even the demo now is careful to show curated but possible things now. they learned their lesson. The code changes are the most common tutorials you can find on the web. Adding a speed slider, the terrain tutorials are literary called "height maps" and focus on making it taller or flatter.
Why would anybody trust this after they faked the last Gemini demo?
Why would anybody trust this after they faked the last Gemini demo?
To be fair, they mostly faked the near instantaneous, real-time flow of the conversations. The answers were, as far as I know, legit. But I still agree that we should be skeptical.
This one seems to be super straightforward about timeliness and capabilities, but the examples might be a bit simpler than people think. This is pretty amazing but like someone else said you could achieve similar results from rag due to the lack of novelty in these questions and the fact that each dealt with pretty independent examples as opposed to using custom code developed elsewhere in the codebase.
Earlier quoted context omitted.
Exactly. Give us access the model and let independant researchers test it. OpenAI did this with GPT4, opening access publicly and deeper access to researchers within and outside of Microsoft. I simply don't believe the model is that good. Otherwise, maybe try to compete with OpenAI directley?
Wonder why they're not just giving us access, if it's indeed so good? Seems it's just to generate some noise and hype around Gemini. Hardly believable after the previous faked demo, as someone already said.
For Microsoft it doesn't make a difference. They are taking their own cash, investing it in OpenAI, and then turning right around and booking it as revenue. As a bonus it makes Google look wrong-footed. But fundamentally Microsoft doesn't care how much money they torch doing this.
Earlier quoted context omitted.
Companies will fire 70% boilerplate coders in following years
Na we’ll all be moved to perpetual on-call, every day an endless fire drill as hundreds of services are launched on top of the crumbling crash looping burning landscape of millions of services launched last quarter, a Mad Max world of endless adrenaline and New Relic AI-enhanced alerts.
I want to see something where we have a big piece of code, and a big standards document it purports to implement, and the system can answer questions like "is this part of the spec implemented? Where it is implemented? What does this piece of code mean (w.r.t. the spec)? If I implemented this part of the spec, where would the changes go?"