And also point out that AI driven price discrimination isn’t anywhere close to negotiated. You’re stuck with the price the machine gives you, with little to no recourse, short of rewriting your entire digital life!
The thing that's missing for me is suggestions on how much to lift / how many reps. There's a fitness program called 100 Pushups that came up with a good solution for that…
- Repeat the exercise (in this case, a push-up) as many times as possible until failure. A person might achieve 8, for example.
- The app comes up with a schedule; every other day, the user is expected to do a set of 3, 4, 3, 3, 5 (with a 2-minute rest between each set)
- The app's schedule has an algorithm that ramps up the reps at a pace that the user can manage — and self-adjusts if the schedule is too easy or too hard…
- until the user can do 100 push-ups at the 6-week period.
If there's any interest in this, I'd be open to discussing a UI and contributing.
Edit: Followed the github issue and found the link!
Obviously, there are often different services that share the same name, but given that Vanta isn't an actual word in the English language, I would think this might be confusing for people.
As a data point of one, I just assumed Vanta (the company) was doing a Show HN today and was confused at first glance.
Did the title of the post change? At first glance the Show HN is a toy wireshark program very far from any Trust Management and compliance
For example - what if someone were to start a company around a fork of LiteLLM? https://litellm.ai/
LiteLLM, out of the box, lets you create a number of virtual API keys. Each key can be assigned to a user or a team, and can be granted access to one or more models (and their associated keys). Models are configured globally, but can have an arbitrary number of "real" and "virtual" keys.
Then you could sell access to a host of primary providers - OpenAI, Google, Anthropic, Groq, Grok, etc. - through a single API endpoint and key. Users could switch between them by changing a line in a config file or choosing a model from a dropdown, depending on their interface.
Assuming you're able to build a reasonable userbase, presumably you could then contract directly with providers for wholesale API usage. Pricing would be tricky, as part of your value prop would be abstracting away marginal costs, but I strongly suspect that very few people are actually consuming the full API quotas on these $200+ plans. Those that are are likely to be working directly with the providers to reduce both cost and latency, too.
The other value you could offer is consistency. Your engineering team's core mission would be providing a consistent wrapper for all of these models - translating between OpenAI-compatible, Llama-style, and Claude-style APIs on the fly.
Is there already a company doing this? If not, do you think this is a good or bad idea?
I don't understand that last sentence. I suspect I'm reading it wrong, but am having trouble parsing it in a way that doesn't mean: this data cannot be explained by a changing media environment since 2020. It's very easy for me to look at the disconnect between survey responses and economic data and see that how people receive and process news is largely responsible for it. The disconnect between facts and opinions has been widely observed, and while the pandemic didn't start it, it seems to have been an accelerator for it.
Individuals experience the world from an individual level — it is easy to go along with any trend that fits your desired narrative because until it is at odds with your individual experience, it doesn’t really matter.
(I’m being a bit reductive and haven’t fully fleshed out this thought, but think the sentiment is accurate)
The solution of filtering after the comment is generated doesn’t seem to address the “paid by the token” piece.
Secondly how do we get to claim that a particular thing is neuromorphic when we have such a rudimentary understanding of how a biological brain works or how it generates things like a model of the world, understanding of self etc etc.