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Claude Fable 5.... just destroyed trading as a profession
New open-source Claude Fable 5.1 Indicator for TradingView made $450,207 in a single day of live trading
The indicator constantly analyzes charts in real time, draws predictions, and highlights potentially good entries. You then decide whether to open a trade or not
The indicator is open-source, and you can try it in the Scripts section of the reverse-engineered TradingView Premium app for Windows and Mac
How can manual traders compete with that?
Want to explore how this AI trading setup works?
1๏ธโฃ Comment.... CLAUDE FABLE 5....
2๏ธโฃ Like and repost
3๏ธโฃ Follow @FutureGirlAi
I'll send you the setup via DM.
Jane Austen retweeted
๐จ AI teammates are no longer just a concept. They're becoming part of how businesses work!
Meet Grok Bot 1.0 ๐ค
Imagine AI teammates that can collaborate across Slack and Teams, join meetings, share knowledge, and take on real responsibilities.
From accounting and customer support to sales and marketing, AI bots are changing the way teams get things done.
And the more they learn, the more helpful they become.
The future of teamwork is looking very different. Are you ready?
Explore what's new: x.ai/news/grok-bot-1-0
Jane Austen retweeted
You don't need to download a virus to get hacked.
Sometimes, one innocent-looking link, one fake login page, or one careless click is enough to expose your personal information.
Hackers don't always break into your device.
Sometimes, they trick YOU into giving them access.
Here are 6 common ways cybercriminals steal personal information and how you can protect yourself. ๐
Jane Austen retweeted
Has anyone gotten an AI agent to work out what's worth saving without being told? Rooting for someone to crack it ๐ฅ
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
Engineers, an agent that redoes every repeat task from zero isn't saving you anything. Check whether yours gets faster the second time round.
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
You'd drop a gym buddy who forgot your routine every single week.
Weird how much we put up with from AI assistants that do exactly that.
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
AI memory isn't about remembering everything.
It's about knowing what actually matters.
๐ค Paid partnership
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
My AI assistant is always ready to take a note, but somehow finding that note later feels like a whole different mission.
I wonder where all those little reminders disappear.
๐ค Paid partnership
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
The real test of a learning agent is not what it remembers. It is what it can do with a task it has never seen before.
That is the bar. Any agent that claims it learned something should be able to prove it on a problem it was not trained on.
This is exactly what Continual ARC goes after, and the results are worth your attention.
๐ค Paid partnership
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
Side-project builders, try giving your agent a short memory file and timing the same job before and after. Easy way to see if memory is doing anything.
๐ค Paid partnership
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
Building an AI agent that can complete tasks is one thing. Building one that can actually learn from experience is a completely different challenge.
Memory and generalization are what separate truly intelligent systems from agents that simply follow instructions. This is an important benchmark for the future of AI.
๐ค Paid partnership
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
Interesting how little most Al assistants carry from one chat to the next.
Feels like the biggest gap left in these tools.
๐ค Paid partnership
OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience.
On Continual-ARC, our new benchmark at @letsunifyai, none of them were able to memorize anything of value and none were able to generalize to new tasks. Training a small 9B model's weights did both.
Jane Austen retweeted
AI Architect Tech Stack for 2026โ27 Explained! ๐
Knowing how to build an AI chatbot is one thing.
Designing an enterprise AI system that scales, stays secure, and works reliably in production is another.
That's where AI Architects come in.
Here are the 9 essential layers you should understand:
โ Programming & Development
Python, TypeScript, C#, SQL, and GitHub form the foundation for building AI applications.
โ Models & AI Platforms
Microsoft Foundry, Azure OpenAI, OpenAI, Anthropic, and Hugging Face provide access to AI models.
โ Agents & Orchestration
Microsoft Agent Framework, LangGraph, Semantic Kernel, CrewAI, and LlamaIndex coordinate agent workflows.
โ RAG & Knowledge Systems
Azure AI Search, Pinecone, Weaviate, PostgreSQL, and Neo4j enable knowledge retrieval.
โ Data & Processing
Microsoft Fabric, Databricks, Snowflake, Spark, and Kafka support enterprise data pipelines.
โ APIs & Integration
FastAPI, Azure API Management, GraphQL, MCP, and Kafka connect AI systems.
โ Cloud & Infrastructure
Azure, AWS, Google Cloud, Docker, and Kubernetes support deployment and scaling.
โ Security & Governance
Entra ID, Purview, Key Vault, OPA, and HashiCorp Vault help protect AI systems.
โ MLOps & Observability
MLflow, GitHub Actions, LangSmith, Arize, and Grafana monitor performance.
The goal isn't to master every tool. It's to understand how the entire architecture fits together.
Which layer are you focusing on?
๐๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฏ๐ฒ๐๐๐ฒ๐ฟ ๐ฎ๐ ๐๐ ๐ถ๐ป ๐ท๐๐๐ ๐ญ ๐บ๐ถ๐ป๐๐๐ฒ ๐ฎ ๐ฑ๐ฎ๐. ๐๐ผ๐ถ๐ป ๐บ๐ ๐๐ฒ๐ฒ๐ธ๐น๐ ๐ป๐ฒ๐๐๐น๐ฒ๐๐๐ฒ๐ฟ ๐๐ต๐ฒ๐ฟ๐ฒ ๐ ๐ฑ๐ผ๐ฐ๐๐บ๐ฒ๐ป๐ ๐๐ต๐ฒ ๐ฟ๐ฒ๐ฎ๐น-๐๐ผ๐ฟ๐น๐ฑ ๐ท๐ผ๐๐ฟ๐ป๐ฒ๐ ๐ผ๐ณ ๐๐ ๐๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป.
๐ ๐ฆ๐ถ๐ด๐ป ๐๐ฝ ๐ณ๐ฟ๐ฒ๐ฒ now โ avsl.beehiiv.com/
Join Me On Youtube And Insta :
Youtube : lnkd.in/e3UVBNSk
Instagram : lnkd.in/ebWK5b6V
Follow @AiswaryaVenkit1 for more such insights!!
Jane Austen retweeted
agents always fall apart the second a real user does something weird
this at least lets you find that out before shipping. digital twin + actual edge cases instead of the usual 5 happy path tests. free too so no reason not to try
๐ค Paid partnership
Big day for us at @pluraiAI ! Plurai Simulation is live and free for every AI engineer.
AI agents look great in demos. Until real users break them.
So we built a world where your agent can fail, learn, and get fixed before your users ever see it.
โ Digital twin: Your real agent, its tools, and environment recreated from your code
โ Simulated users & tasks: Realistic users, tasks, and workflows that push your agent into the edge cases that matter
โ Auto evals: Check what your agent actually did, not just what it said
โ Verified fixes: Every failure comes with the run that exposed it and a fix you can verify
โ Replays: Turn any production failure into a simulation and replay it against every new version of your agent
All inside the coding agent you already use: @claudeai code, @OpenAICodexCli , or @GitHubCopilot .
Start simulating for free: simulation.plurai.ai/connect
Jane Austen retweeted
Sex with a beginner:
Her: Donโt stop.
Him: (switches positions)
Sex with a pro:
๐จ You're probably using Gmail just to send and receive emails.
But Gmail can do MUCH more than that!
From managing your inbox to saving time and staying organized, these simple Gmail tricks can make your daily life easier.
Here are 7 powerful Gmail tips everyone should know.
Jane Austen retweeted
I'd hand an agent a text-to-object job after seeing 84.05. I wouldn't hand it a stateful workflow at 30.26.
Can coding agents replace traditional 3D vision pipelines and build a entire interactive worlds from code?
Introducing Einsia AI's Frontier3DBench โ a unified benchmark evaluating coding agents across 3D Objects, Scenes, and Interactive Open Worlds.
- 145 tasks across 9 categories (Blender & UE5)
- 11 frontier model-harness configurations
- Joint evaluation: Appearance, Structure & Behavior
Project: lab.einsia.ai/frontier3dbencโฆ
GitHub: github.com/Einsia/Frontier3D
paper:lab.einsia.ai/frontier3dbencโฆ
๐งต See key findings below ๐
Jane Austen retweeted
Major landlords are quietly rolling out AI rent software across America that could either modernize apartment pricing or permanently raise the cost of housing for working families.
Starting in high-density markets heading into 2027, traditional negotiated rents are being replaced by cloud-connected algorithms. Raise the price of a two-bedroom by 10 percent the week occupancy dips below 95 percent. Hold rents firm during slow months instead of offering free parking or reduced deposits. Coordinate increases across competing buildings so no one undercuts the market.
Every price recommendation happens wirelessly in seconds from a central dashboard. No leasing manager has to call competitors or survey the street.
RealPageโs YieldStar and AI Revenue Management tools have already been used on millions of units. Large operators fed non-public lease and occupancy data into the system. Courts later approved nearly $360 million in settlements with dozens of landlords. The Department of Justice also restricted how the software can use competitor data.
This is not normal market supply and demand. This is algorithmic coordination built directly into the buildings where families sign leases.
Last year investigators and former industry employees described how the system works. What they shared changed how many renters look at a lease renewal.
โLandlords just turned independent buildings into shared pricing networks. The question is not whether operators will use the software, because they already spent years integrating it. The question is how much extra a family will pay every month simply because the algorithm sees tight occupancy across the whole submarket.โ
Here is how the rent algorithm actually works, how it uses shared data, and the exact steps you need to check your building and negotiate against it.
Technology is not just changing the way we live; it is transforming the way we think, learn, and connect with the world. ๐โจ
We are living in an era where innovation opens new doors, creativity has no limits, and artificial intelligence is creating incredible opportunities for everyone. ๐
The future belongs to those who are willing to learn, adapt, explore, and embrace new ideas. Every small step toward knowledge brings us closer to a smarter and brighter tomorrow.
Stay curious, keep learning, believe in innovation, and never stop growing. Because the world is moving forward, and the best way to be part of the future is to prepare for it today! ๐กโค๏ธ
Embrace Technology. Inspire Innovation. Build the Future. ๐ฅ
#Technology #ArtificialIntelligence #Innovation #DigitalWorld #FutureTechnology #AI #Knowledge #SmartFuture
























