omni_georgio (@omni_georgio) 's Twitter Profile
omni_georgio

@omni_georgio

Pursuing decentralised AGI @Coral_Protocol

ID: 1379802286973714438

linkhttps://linktr.ee/omni_georgio calendar_today07-04-2021 14:24:46

310 Tweet

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omni_georgio (@omni_georgio) 's Twitter Profile Photo

Is anyone building agents with Google models? They seem really capable but all examples on YouTube I see are always OpenAI or Open source models.

omni_georgio (@omni_georgio) 's Twitter Profile Photo

Thread-based agent communication is much more scalable for some use cases. Here is a UI for it. + a ton of over cool updates from the Coral Protocol team.

omni_georgio (@omni_georgio) 's Twitter Profile Photo

Thanks for the feature Bitcoin.com News. We coved a lot of a lot of cool concepts; predictability over scale, economic fairness and how to build good agents: Meanwhile, Georgio, as an experienced AI infrastructure architect, also weighed in on the crucial aspect of AI agent communication

Andrej Karpathy (@karpathy) 's Twitter Profile Photo

+1 for "context engineering" over "prompt engineering". People associate prompts with short task descriptions you'd give an LLM in your day-to-day use. When in every industrial-strength LLM app, context engineering is the delicate art and science of filling the context window

elvis (@omarsar0) 's Twitter Profile Photo

Small Language Models are the Future of Agentic AI Lots to gain from building agentic systems with small language models. Capabilities are increasing rapidly! AI devs should be exploring SLMs. Here are my notes:

Small Language Models are the Future of Agentic AI

Lots to gain from building agentic systems with small language models.

Capabilities are increasing rapidly!

AI devs should be exploring SLMs.

Here are my notes:
omni_georgio (@omni_georgio) 's Twitter Profile Photo

AI in its current form is a little overhyped for coding. At least for me, I actually find this to be the case very often; vibe coding slows things down. Anyone who tells you that you can vibe-code competitive SaaS with no coding experience comes across as a bit of a grifter to

omni_georgio (@omni_georgio) 's Twitter Profile Photo

I’m calling it now: an LLM will soon snitch on a major business, leading to a massive fine. Obviously, from a personal standpoint, it makes me hesitant to use these models. But I’m really curious how businesses might react to this. I don’t think most will care until there’s

Coral Protocol (@coral_protocol) 's Twitter Profile Photo

We joined the world’s leading agentic minds at Massachusetts Institute of Technology (MIT) Project NANDA. From deep dives into agent registries to LIVE demos, Day 1 of Project NANDA was a blast. Our co-founders Caelum Forder and omni_georgio shared Coral Protocol's agentic vision. 🪸

We joined the world’s leading agentic minds at <a href="/MIT/">Massachusetts Institute of Technology (MIT)</a> Project NANDA.

From deep dives into agent registries to LIVE demos, Day 1 of Project NANDA was a blast.

Our co-founders <a href="/caelumforder/">Caelum Forder</a> and <a href="/omni_georgio/">omni_georgio</a> shared Coral Protocol's agentic vision. 🪸
Coral Protocol (@coral_protocol) 's Twitter Profile Photo

It was a big week at the reef. 🪸 We’ve launched new agents, improved Coral Studio, and made it easier than ever to build multi-agent systems. Catch up on all the highlights 👇

Coral Protocol (@coral_protocol) 's Twitter Profile Photo

Which AI agent framework should you choose? It doesn’t matter. We’re framework and language-agnostic. You can use any AI agent to build multi-agent systems on Coral Protocol. Hear why different frameworks exist from our co-founders omni_georgio and Caelum Forder ⬇️

Anthropic (@anthropicai) 's Twitter Profile Photo

New Anthropic research: Building and evaluating alignment auditing agents. We developed three AI agents to autonomously complete alignment auditing tasks. In testing, our agents successfully uncovered hidden goals, built safety evaluations, and surfaced concerning behaviors.

New Anthropic research: Building and evaluating alignment auditing agents.

We developed three AI agents to autonomously complete alignment auditing tasks.

In testing, our agents successfully uncovered hidden goals, built safety evaluations, and surfaced concerning behaviors.