AmyFletcher

A decade of Sticky Rice in Knoxville began with refugee journey from Laos knoxnews.com/story/entertai…

Nvidia CEO says robotics is South Korea's next big sector, points to 'some suprises' reut.rs/4afeO7P reut.rs/4afeO7P

Japan proposes rebuilding ageing nuclear plants to meet power demand reut.rs/4uBiBE5 reut.rs/4uBiBE5

The Day the Earth Stood Still (1951)

Everyone is talking about AI tools. But the real shift is happening somewhere else. Agentic AI. Not just models that answer questions… But systems that plan, decide, act, learn, and improve on their own. Here’s the bigger picture most people miss 👇 AI evolution looks like this: AI & ML ➡️ Turn data into predictions Deep Learning ➡️ Neural networks solve complex tasks Gen AI ➡️ Create text, images, audio, video AI Agents ➡️ Execute tasks autonomously Agentic AI ➡️ Run entire workflows end-to-end What makes Agentic AI powerful? • Multi-agent collaboration • Goal decomposition • Planning and reasoning • Tool use and function calling • Memory systems (short + long term) • Self-reflection and error recovery • Feedback loops for improvement • Long-term autonomy In simple terms: Old AI: “Tell me the answer.” GenAI: “Generate something for me.” Agents: “Do this task.” Agentic AI: “Handle the whole process.” This is how companies will soon automate: • research • marketing workflows • customer operations • coding pipelines • data analysis • decision systems The future of AI isn’t just smarter models. It’s autonomous systems working together. And we’re only at the beginning. 🚀 Follow @MeenakshiYACS for more such posts #AI #AgenticAI #AIAgents #GenAI #ArtificialIntelligence #Automation

Harvard Business Review on why agentic AI advantages startups: they design around agents from day one. Large orgs retrofit agents into workflows built for humans. Changes what a small team can handle. via Harvard Business Review hbr.org/2026/07/how-ag…

Announcing my new course: Agentic AI! Building AI agents is one of the most in-demand skills in the job market. This course, available now at deeplearning.ai, teaches you how. You'll learn to implement four key agentic design patterns: - Reflection, in which an agent examines its own output and figures out how to improve it - Tool use, in which an LLM-driven application decides which functions to call to carry out web search, access calendars, send email, write code, etc. - Planning, where you'll use an LLM to decide how to break down a task into sub-tasks for execution, and - Multi-agent collaboration, in which you build multiple specialized agents — much like how a company might hire multiple employees — to perform a complex task You'll also learn to take a complex application and systematically decompose it into a sequence of tasks to implement using these design patterns. But here's what I think is the most important part of this course: Having worked with many teams on AI agents, I've found that the single biggest predictor of whether someone executes well is their ability to drive a disciplined process for evals and error analysis. In this course, you'll learn how to do this, so you can efficiently home in on which components to improve in a complex agentic workflow. Instead of guessing what to work on, you'll let evals data guide you. This will put you significantly ahead of the game compared to the vast majority of teams building agents. Together, we'll build a deep research agent that searches, synthesizes, and reports, using all of these agentic design patterns and best practices. This self-paced course is taught in a vendor neutral way, using raw Python - without hiding details in a framework. You'll see how each step works, and learn the core concepts that you can then implement using any popular agentic AI framework, or using no framework. The only prerequisite is familiarity with Python, though knowing a bit about LLMs helps. Come join me, and let's build some agentic AI systems! Sign up to get started: deeplearning.ai/courses/agenti…

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@letitbeeetle They had vaulted past mop top here into a realm of cool so rarefied that 60 years later they remain the only inhabitants to reach that planet. And the gang is so tight, too, just the four of them facing down the world. Glad I had seats to the show.

IM CRYING what are these questions😭😭

Fair questions, and right now I don't trust the DNC personally to organize a 2-car parade. That said, isn't it possible that something like this could work like the Alaska oil revenue fund? I think the premise--the public stake and investment in the underlying infrastructure--is somewhat similar.

How would board meetings work here. Who represents that 50%

I can see that, and its worked in the past, but what if the "new jobs created" equation does not work in the case of AI? If AI is a new case of job decimation without new roles created, then the wealth disparities become dangerous and untenable, potentially toppling us over into hard-left insanity as the middle-class evaporates.

@ForesightMe @draecomino Nope. Not even close. If the government focuses on keeping markets competitive, prices will go down for consumers, which is a more efficient way of giving people a "handout".

Why is there always such passion for redistributing things created but zero passion for creating things in the first place??

@BobDon320 @draecomino Fair point.

@ForesightMe @draecomino Nikola Tesla? Great inventor. Inept at business. Died penniless.

Four pillars of ethical governance for #fintech #foresight (transparency, inclusion, resilience, and anticipation).

CONGRATS AGAIN to "THE REALITY ENGINEER" by Konstantin, an Honorable Mention, in the Internet Archive’s 2026 Public Domain Film Remix Contest 🏅 A comedic short about a scientist who attempts to improve human life by altering reality, only to find that each well-intentioned fix deepens the chaos. Watch the full short film ⤵️ archive.org/details/the-re… #PublicDomain #PublicDomainDay

@robbysoave Okay, that's good. Well-played.

Okay uhh... well now that we are 50% shareholders in this whole AI thing, we must object even more strongly to the data center moratorium—also backed by Sanders!—which would shrink our profits. (This points to the incoherence of the Sanders position.)

3 ways to overcome your fear of disruption wef.ch/1SmvGrg #technology

Meet Alberto Privitera, Tenure-Track Assistant Professor at the University of Florence, and Foresight Fellow 2026. Alberto is exploring how light and spin can be harnessed in molecules to advance quantum technologies and solar energy conversion. His work sits at the intersection of chemistry, physics, and materials science, with implications for how we generate energy and next generation computing. Alberto is currently establishing his research group in Florence, supported by the ERC and FIS2 starting grants. Learn more about his work at priviteragroup.com Feel free to reach out to Alberto if you would like to discover how chemistry can develop new quantum computers or future solar cells.

Ok, this is funny 😂🤣😂