FELIX

chat dau @openai | ex-@tryramp, @uclanlp

[FELIX @fel9z]

@0xDesigner @jxnlco the glaze has gone too far 😂

[joowon @n0w00j]

Today, Melius is launching the new way for creatives to work with agents.

Introducing the slash command.

Creative work with agents painfully moves one step at a time. Each idea is queued sequentially, so even a full campaign only moves at the pace of a single agent. Your eyes flips back and forth between the chat constantly.

Slash changes that.

Hit the slash key anywhere on the canvas to start an agent on a task. Run as many as you want, side by side. Each agent works in parallel, each with a clear status showing its progress.

Every designer, marketer, and director will be that much more productive - building images, videos, audio and more at the speed of thought.

Try it now on Melius.

[FELIX @fel9z]

@realJessyLin very cool!

[FELIX @fel9z]

@daniel_tian1 @GradientVC cool

[FELIX @fel9z]

@rahulgs let him cook 🔥

[Nike Basketball @nikebasketball]

Sleep well, NY.

[FELIX @fel9z]

@benhylak @RemindMe 6 months

[FELIX @fel9z]

Thoughtful piece https://t.co/HtEnBcljMD

[FELIX @fel9z]

Yet CS enrollment is at all time lows across the nation, how did we get here? @colossusmag

[NatSecKatrina @natseckatrina]

I would gently push back on the underlying premise that if the government agrees to a usage policy restriction, that's ironclad, but if it's just a law or policy, that's no guarantee at all. Why would Anthropic think that their earlier usage policy forbidding surveillance was sufficient to guarantee their models could not be used for this?

My main argument is that usage policies are only one part of a layered set of safeguards. Here's how I think about this:

1. The safety stack travels with the model. The Department was not asking us to modify how our models behave. Their position was, build the model however you want, refuse whatever requests you want, just don't try to govern our operational decisions through usage policies. For whatever risk surface area remains, our safety stack, refusal policies, and guardrails become another protection. And those technical controls are often more reliable than contract clauses anyway. Our contract gives us control over the models and safety stack we deploy, and the ability to improve them over time.

2. AI experts directly involved. Instead of hoping contract language will be enough, our contract allows us to embed forward deployed engineers, commits to giving us visibility into how models are being used, and we have the ability to iterate on safety safeguards over time. If our team sees that our models aren't refusing queries they should, or there's more operational risk than we expected, our contract allows us to make modifications at our discretion. This gives us far more influence over outcomes (and insight into possible abuse) than a static contract provision ever could.

3. U.S. law already constrains the worst outcomes. We accepted the “all lawful uses” language proposed by the Department, but required them to define the laws that constrained them on surveillance and autonomy directly in the contract.  And because laws can change, having this codified in the contract protects against changes in law or policy that we can’t anticipate.

[The White House @WhiteHouse]

👀

💊https://t.co/jjnWOhbKzY

[Midjourney @midjourney]

Niji V7 is now live. This model features improved anime coherence, prompt understanding, text rendering, and sref performance. Enjoy!

[OpenAI Developers @OpenAIDevs]

📣Calling all app developers! Starting today, you can submit your ChatGPT app for review.

Approved apps will be listed in the app directory, a new surface for users to search for apps directly in ChatGPT. https://t.co/bO1OfXb0Em

[FELIX @fel9z]

@tamaybes incentives + CTO diff

[FELIX @fel9z]

@emollick I know a hex notebook when I see it 😍

[FELIX @fel9z]

@eglyman @djtokyo @Fukahire109 @taro_f sumatokado is SO back 🇯🇵

[FELIX @fel9z]

@ericjang11 @IGGYAZALEA bull signal

[Sebastian Raschka @rasbt]

> I think the community still has to discover how and when finetuning makes sense compared to the (often strong) baseline of prompting a giant model.

Agreed. But for mid-size companies, there’s now also the option to finetune AND prompt a giant model (thanks to all the recent giant open-weight LLMs).

Based on my interactions with companies out there, it’s often to narrow the scope and specialize like you said. But then also having full control over model and data. Some of it is for ideological reasons, some of it is mandatory security and privacy compliance.

[FELIX @fel9z]

@n0w00j u know my # bro 😭

[FELIX @fel9z]

@n0w00j @eglyman @tryramp @karimatiyeh Bitch don’t tell me u b2b,unless u been in Fortune