Prism and Higgsfield are both similar in that we bring many AI models into one place. Higgsfield is focused on a number of different use cases - storyboarding, ai filmmaking, and visual effects - while Prism is hyper-focused on short form video.
This is a great point, and I agree with you. If a weight loss supplement brand were to use an AI influencer to market their product, it does raise questions about whether their supplement does in fact work on real people.
Nevertheless, things are trending more in this direction, and AI influencers will soon become the norm. Brands should be required to disclose when their marketing is AI.
It's worth mentioning that AI videos on Prism (and on any platform) do not have to be purely prompt to creative. For example, a brand designer can take an existing creative for a billboard for example and then use AI to generate images of this creative at a train station, in the Louvre, at a bus stop etc (without actually going there and shooting images).
This is a great point. It is challenging to know which models are good at what.
We've found that Seedance is good at photorealitic faces, Kling is fantastic at generating audio (highest quality model in terms of syncing character's face to the words they say imo), and Sora is great at UGC.
nice, fal is solid. whats the pricing like compared to calling the model APIs directly?
lots of people are asking for my script so i'm open sourcing it fairly soon (openslop.ai if you want to get notified). currently integrating with runware, elevenlabs, cartesia, kling, runwayML but will look into integrating with fal too. would you be open to connecting to helping with integration with fal?
Good question. We don’t define “wrong tool” in some universal way, because that really depends on the workflow.
What we do in practice is let the team mark a few tool calls as right or wrong in context, then use that to learn the pattern for that agent. From there, we can flag similar cases automatically by looking at the convo state, the tool chosen, the arguments, and what happened next.
So we’re learning what “correct” looks like for your workflow and then catching repeats of the same kind of mistake.
This is a great point. I'm assuming when you mention blast radius you're mentioning the risk of the account being banned for being a bot.
One risk with these new standards for agent auth - which we will of course support if our customers want it - is that the websites that need them the most are the least likely to adopt them.
The main use cases for browser agents are for paying utility bills on old government websites or finding receipts for an expense report on a website without an API. There is a no reason to use browser agents on a website like Linear for example. A developer is better off integrating via API or MCP.
Therein lies the main challenge; the websites where browser agents are most useful are the same websites that are least likely to adopt new technology (it was their not adopting new technologies that made them good candidates for this browser agents in the first place).
I think this new standard is awesome, but I fear that the websites that support it will be those websites that didn't need it in the first place (because they could just as easily add an API).
For blast radius, it's also the risk of the bot doing something wrong because it's overprivileged for the task. But yes, getting banned is a problem too.
I see what you're saying here, this is a "Plaid, for everything else on the web" move. Interesting!
We setup an agent mailbox with Agentmail (https://agentmail.to/). Whoever owns the account (likely the developer) sets up a forwarding rule to this account.
When our agent signs in, we input the forwarded otp code to get access.
