Earlier quoted context omitted.
Their data retention policy on their APIs is 30 days, and it's not used for training [0]. In addition, qualifying use cases (likely the ones you mentioned) qualify for zero data retention for most endpoints. [0] - https://platform.openai.com/docs/models/how-we-use-your-data
the policy says that, but there is no external verification or auditing. So its hard to trust.
OpenAI is too cheap to beat
301–310 of 426 posts
Re: OpenAI is too cheap to beat
#302Earlier quoted context omitted.
For years people have essentially made a living off FUD like "ignore the literal legal agreement and imagine all the worst case scenarios!!!" to justify absolutely farcical on-premise deployments of a lot of software, but AI is starting to ruin the grift. There are some cases where you really can't afford to send Microsoft data for their OpenAI offering... but there are a lot more where some figurehead solidified the…
Gah, this is just not how it works. You are probably right that e.g. patient information, private conversations, proprietary code, etc would be safe with OpenAI. But it's not the on-prem team that needs to convince the rest of the organization to keep things on prem. Quite the opposite -- every single tech person would love to make our data someone else's problem (and get a big career boost from dealing with cloud te…
This nonsense that you can't trust anyone with your data is completely unfounded
Re: OpenAI is too cheap to beat
#303The premise of this is flawed. OpenAI is cheap because of has to be right now. They need to establish market dominance quickly, before competitors slide in. The winner of this horse race is not going to be the company with the best performing AI, it’s going to be the one who does the best job at creating an outstanding UX, ubiquitously presence, entrenching users, and building competitive moats that are not feature d…
I just took Lyft again to the airport earlier this month same location and I was billed $49 USD, and a $1.30 “Texas Surcharge”.
An inflation calculator says that $38 usd in 2015 is equivalent to $49 in 2023. Color me surprised. I thought the prices had significantly increased since I signed up but it looks like actually no they didn’t.
Trawling back through those old emails I do see constant “50% off all weekday rides” offers from the time I signed up until about March 2016, at which point they stopped. So there were some subsidized incentives when they were early in Austin but it looks like they stopped sometime in early 2016. So if the money train existed, it happened before that, at least in Austin.
Re: OpenAI is too cheap to beat
#304The premise of this is flawed. OpenAI is cheap because of has to be right now. They need to establish market dominance quickly, before competitors slide in. The winner of this horse race is not going to be the company with the best performing AI, it’s going to be the one who does the best job at creating an outstanding UX, ubiquitously presence, entrenching users, and building competitive moats that are not feature d…
But OpenAI appears to have some sort of data moat. I doubt their model is the best in the world, but more/better data generally beats better model, and GPT-4 definitely beats Claude, Bard, Bernie and the rest probably because they curated the best quality and largest data set. Maybe that moat doesn't last long but perhaps they have exclusive rights to some of that dataset through commercial agreements that could be a…
For what reason do you doubt that?
Re: OpenAI is too cheap to beat
#305Earlier quoted context omitted.
> My uninformed opinion is that Google and Meta's ML efforts are fragmented - It seems more likely that at Google at least they just fell into the classic innovator's dilemma in which they were stuck trying to apply innovation to their current business models in an attempt at incremental innovation instead of seeking an entirely different customer and market.
Yeah, same with Meta. Both have a large graveyard of failed innovation attempts. Remember Google Buzz? Google Plus?
Re: OpenAI is too cheap to beat
#306Earlier quoted context omitted.
The difference between openai and next best model seems to be increasing and not decreasing. Maybe Google's gemini could be competitive, but I don't believe open source will match OpenAI's capability ever. Also OpenAI gets significant discount on compute due to favourable deals from Nvidia and Microsoft. And they could design their server better for their homogenous needs. They are already working on AI chip.
Being ahead in a race doesn’t mean you’re going to win. Open source models will win eventually because they have the lowest marginal cost to run. People will figure out what OpenAI is doing and duplicate it. There’s many people working at OpenAI, it’s going to leak out.
Re: OpenAI is too cheap to beat
#307The premise of this is flawed. OpenAI is cheap because of has to be right now. They need to establish market dominance quickly, before competitors slide in. The winner of this horse race is not going to be the company with the best performing AI, it’s going to be the one who does the best job at creating an outstanding UX, ubiquitously presence, entrenching users, and building competitive moats that are not feature d…
Re: OpenAI is too cheap to beat
#308Earlier quoted context omitted.
Depends how you define quality. This paper reflects my own experience https://arxiv.org/abs/2305.08377 and shows how LLM technology has a lot more to offer than "ChatGPT". The real takeaway is that by training LLMs with real training data (even with a "less powerful" model) you can get an error rate more than 10x less than you get with the "zero shot" model of asking ChatGPT to answer a question for you the same way…
Moore's law is irrelevant. Large language models are going to leave the digital paradigm behind altogether. Neural nets don't need fully precise digital computing. Especially with quantization we're seeing that losing a bit of precision in the weights isn't impactful. Now that we're serving huge foundation models with static weights there's an enormous incentive to develop analog hardware to run them. Mark my words,…
It really depends where you draw the lines, because you could also say that one single transistor in my electrical CPU is doing a kerjillion calculations for all of the atoms and electrons involved.
Re: OpenAI is too cheap to beat
#309Earlier quoted context omitted.
Pretty obvious to most that switching cloud providers is not quick or painless for the majority of orgs. There's not really an argument in good faith to suggest otherwise. Especially given that many orgs use managed or cloud specific solutions that have no 1:1 mapping between vendors
I said I'd have to change that one managed resource. Actually it's two - the managed database. But no more.
As someone who worked on a similar project recently, I'm getting that idea that you obviously don't know what you're talking about.
Re: OpenAI is too cheap to beat
#310The premise of this is flawed. OpenAI is cheap because of has to be right now. They need to establish market dominance quickly, before competitors slide in. The winner of this horse race is not going to be the company with the best performing AI, it’s going to be the one who does the best job at creating an outstanding UX, ubiquitously presence, entrenching users, and building competitive moats that are not feature d…
The winner is going to be the consumers of AI. It's a race to the bottom on pricing on the provider/infra side. It seems very unlikely that any single LLM provider will achieve a sustained and durable advantage enough to achieve large margins on their product. Consumers can swap between providers with relative ease, and there is very little stickiness to these LLM APIs, since the interfaces are general and operate on…