Generative AI

LIVE SESSION - SPECIAL EPISODE The follow-up to our most-popular LinkedIn Live from last year, featuring the founders and hosted by Samuel Cummings, to discuss what’s changed in AI and what’s worth building or backing right now. 🔥Only 2 days left: GenAI Works is raising capital through our Reg CF campaign. Learn more here: https://lnkd.in/g6YVkRSi Minimum investment: $1,000 | Class B Common Stock* In this live session, we’ll explore: - How agentic AI is shaping the future of work and enterprise workflows - What today’s smartest investors are watching in AI infrastructure and orchestration - The rise of systems designed for multi-agent interoperability and governance 𝐖𝐞𝐝𝐧𝐞𝐬𝐝𝐚𝐲, 𝐀𝐮𝐠 27 – 10 𝐀𝐌 𝐏𝐓 𝐎𝐧𝐥𝐢𝐧𝐞 - 𝐅𝐫𝐞𝐞 𝐫𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 Hosts: 𝐒𝐭𝐞𝐯𝐞 𝐍𝐨𝐮𝐫𝐢 – 𝐂𝐄𝐎, 𝐅𝐨𝐮𝐧𝐝𝐞𝐫 & 𝐃𝐢𝐫𝐞𝐜𝐭𝐨𝐫 Global AI leader, ranked among the top 10 authorities in AI and Data Science, with 2M+ followers. Australia’s ICT Professional of the Year, founder of AI4Diversity, and a leading voice on responsible AI adoption. Steve’s mission is to build the world’s largest AI community, empowering society to thrive in an AI-enabled future. 𝐑𝐨𝐭𝐞𝐦 𝐀𝐥𝐚𝐥𝐮𝐟 – 𝐂𝐨-𝐅𝐨𝐮𝐧𝐝𝐞𝐫, 𝐃𝐢𝐫𝐞𝐜𝐭𝐨𝐫 & 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐀𝐝𝐯𝐢𝐬𝐨𝐫 AI pioneer and serial entrepreneur with over a decade of experience building large-scale AI systems across defense, finance, and tech. A recognized thought leader, Rotem envisions a future where humans and AI agents work together strategically and equitably, and regularly shares his expertise at global events. 𝐒𝐚𝐦𝐮𝐞𝐥 𝐉. 𝐂𝐮𝐦𝐦𝐢𝐧𝐠𝐬 𝐈𝐈𝐈 – 𝐃𝐢𝐫𝐞𝐜𝐭𝐨𝐫 𝐨𝐟 𝐄𝐝𝐮𝐜𝐚𝐭𝐢𝐨𝐧 Award-winning data scientist, keynote speaker, and thought leader in digital empathy and data-driven strategy. With over a decade in AI, strategic enablement, and predictive modeling, Sam has led innovation in education at GenAI.Works. He has delivered keynotes at global events like WICT Tech It Out and ABET, and created top-rated LinkedIn Learning courses that help professionals harness AI and data for growth. *This Reg CF offering is made through DealMaker Securities LLC. Investing involves risk, including loss of principal.

New data drop from Google Cloud👇 88% of early adopters are already seeing ROI from gen AI. So where are AI agents actually getting deployed? Out of 1,800+ orgs already using them, here’s the cross-industry snapshot: 49% → Customer experience (support, field ops, self-service) 46% → Marketing + Cybersecurity (content + compliance = hot zones) 43% → R&D + Product design 40% → Software engineering 38% → Finance & accounting 15% → Legal (late to the party, high stakes) What stands out? → Customer service leads the charge. Not surprising, AI here saves time, scales fast, and drives measurable NPS gains. → Security & tech support are next. Agents don’t sleep, threat detection and triage are built for them. → Innovation workflows are getting rewired. From research agents to multi-agent product design stacks. → Legal & HR? Still early innings. High opportunity. High friction. Huge upside for whoever gets it right first. ⚙️ If you’re not deploying agents yet, you're losing operational surface area every quarter. The companies winning aren’t just building agents. They’re redesigning processes around co-working with AI. What’s the first non-obvious business function in your org that an AI agent could quietly take over… better than a human? Own a piece of agentic AI innovation. GenAI Works is raising capital through our Reg CF campaign. Minimum investment: $1,000 | Class B Common Stock Invest now: https://hubs.li/Q03HJzmd0 This Reg CF offering is made through DealMaker Securities LLC. Investing involves risk, including loss of principal. #aiagents #genai #agenticai #googlecloud #aiforenterprise #futureofwork #automation

💡BREAKING: This NEW paper literally came up with a system that turns research papers into AI agents. Paper2Agent is a fully functional agent that reads the paper, understands the code, installs dependencies, validates results and then lets you run the paper’s methods using natural language. (Read the paper here: https://hubs.li/Q03Ht7_q0 ) Here's how it works:👇 1. You give it a paper (PDF + GitHub link). 2. It spins up a Model Context Protocol (MCP) server with: - Tools that reproduce the paper's methods - Structured data & code resources - Prompt templates for key tasks 3. It deploys everything remotely (e.g. Hugging Face). 4. You connect a chat agent (like Claude Code) and ask questions like: “Apply this method to my dataset.” “Reproduce figure 3.” “Compare gene expression across tissues.” In testing, it recreated AlphaGenome, Scanpy, and TISSUE into agents that: ✅Matched human outputs with 100% accuracy ✅Ran entire pipelines via chat ✅Even challenged the original conclusions with fresh insights No setup. No coding. Just smart, scientific copilots, ready out of the box. If you could turn one paper into an AI agent today, which one would it be? Own a piece of agentic AI innovation. GenAI Works is raising capital through our Reg CF campaign. Minimum investment: $1,000 | Class B Common Stock Invest now: https://hubs.li/Q03Htcvw0 This Reg CF offering is made through DealMaker Securities LLC. Investing involves risk, including loss of principal. #airesearch #agenticai #aiagent #machinelearning #artificialintelligence

🔥MCP-UI upgrades AI beyond text conversations Most AI assistants today reply with long text. With MCP-UI, they can now show interactive screens inside the chat. ✅ Shopping → See products with images and prices, then click Add to Cart ✅ Travel → Pick your flight seat from a seat map instead of typing numbers ✅ Food → Browse menus with photos and ratings, then order directly Why this matters People are used to apps that are visual and easy to click. Reading through text or typing commands feels slow, MCP-UI makes AI chats look and work more like apps. 💡How it works → Developers send AI a small “UI package” called a UIResource → The chat displays it safely inside a mini app window → When you click or type, your action goes back to the AI so it knows what to do next Key Features → Safe and secure (everything runs in a sandbox) → Works with popular programming languages like TypeScript and Ruby → Can run on different AI platforms → Flexible enough for any custom workflow 🚀Big Picture With MCP-UI, you don’t need to switch between a chatbot and an app. AI does the thinking, and the UI makes it easy for you to act. This opens the door for smarter shopping, smoother booking, and better collaboration tools. 👉 Explore the repo: https://hubs.ly/Q03HsNF_0 ❓Does adding UI to AI mean progress, or are we looping back to where we started? Built an AI tool? Get it featured in our 13M+ community. Submit here: https://hubs.ly/Q03HsLfy0 #mcp #ui #artificialintelligence #machinelearning

🚨 AI agents are growing up. And they’re not just doing your tasks, they’re building your workflows. Google Cloud’s latest 2025 report outlines 3 clear stages of AI agent maturity every business leader and AI practitioner should understand: Level 1️⃣ – Simple Tasks Think chatbots, image generation, data lookup. Easy wins. Low complexity. Level 2️⃣ – AI Agent Applications Creative agents, customer support bots, email writers. Still scoped, but tied to business value. 63% of execs report better customer experience from agents at this stage. Level 3️⃣ – Multi-Agent Workflows This is where it gets real. Agents that collaborate, orchestrate, and run complex workflows with humans in the loop. 88% of early adopters here are already seeing ROI. And the early adopters? They’re not dipping their toes. 🔹82% have deployed 10 or more agents 🔹39% of IT budgets are now AI-focused 🔹Entire business functions are being rearchitected Agentic AI is shaping up to be the next layer of enterprise infrastructure. So the question isn’t “what can agents do?” It’s “how do we architect teams of agents that move like organizations?” What’s holding most companies back from hitting Level 3? Deploy your own Model Context Protocol server and unlock real-world GenAI workflows. Get started: https://hubs.li/Q03HrY6r0 #agenticai #aiagent #googleai #artificialintelligence #machinelearning

Breaking: Agents Enter the Workforce. Factories Rise to Run Them. This week AI moved deeper into the fabric of work and culture. Salesforce confirmed that agents are no longer experiments but the front line, handling millions of cases once done by people. Cisco and NVIDIA revealed the Secure AI Factory, the kind of infrastructure that will anchor this new workforce. OpenAI researchers traced why models hallucinate, exposing flaws in how they are trained and tested. XPENG showed AI mobility stretching from roads to skies. And in a landmark move, Anthropic reached a settlement with authors, an early sign that the future of creativity and machine learning will be negotiated, not assumed. #ai #ainews #generativeai #openai #anthropic

OpenAI is betting big on the silver screen. The company is backing Critterz, an AI-generated animated film produced with Vertigo Films and Native Foreign. 👉Budget: under $30 million. Timeline: nine months instead of the usual three years. Premiere: Cannes. For Hollywood, the economics are hard to ignore. ✅Traditional animated features often cross the $100M mark and require armies of artists ✅Critterz is being built by a 30-person team, with AI compressing workflows once thought untouchable. The film’s success or failure could become a bellwether: proof that AI can deliver big-screen entertainment at scale, or evidence that the technology isn’t ready to shoulder Hollywood’s creative risks. Studios are watching. Investors are watching. Creatives are watching. If AI can deliver a Cannes-ready film at a fraction of the cost, is this Hollywood’s next disruption, or a one-off experiment? Credits: The Wall Street Journal See what won. See what’s next. Top builds and breakout demos from the hashtag#LeadWithAIAgents Hackathon 2025. Watch now: https://hubs.li/Q03HhkZk0 #aiart #creativeai #artificialintelligence #machinelearning #aiethics #aimovie

🚨 Breaking: AI just helped engineer a material as strong as steel but lighter than Styrofoam. Researchers used Bayesian optimization (AI) to redesign carbon nanolattices at the nanoscale. Instead of uniform beams that fail at weak points, the AI generated non-intuitive geometries that eliminated stress hot spots. ➡️The payoff: 1. 118% stronger, 68% stiffer than conventional designs at the same density 2. Record-breaking specific strength (2.03 MPa·m³/kg) 3. Scalable from nanometers to millimeters, balancing on a bubble yet supporting over a million times its weight ➡️Why it matters: 1. Aerospace: lighter planes and rockets → less fuel, more range 2. Defense: materials that absorb energy without adding weight 3. Energy & mobility: stronger, lighter structures for EVs, batteries, wind turbines 4. Sustainability: massive weight reduction = lower emissions AI is essentially rethinking the physics of materials themselves. If AI can already reinvent matter at this scale, what long-standing engineering limits will it erase next? Built an AI tool? Get it featured in our 13M+ community. Submit here: https://hubs.li/Q03HgvxB0 #physics #aiengineering #generativeai #artificialintelligence #machinelearning

🚨 OpenAI drops paper on why LLMs hallucinate and it’s not what you think. The core finding: hallucinations aren’t mysterious glitches. They’re the natural outcome of how we train and score models. 🔹Pretraining: Even with perfect data, the math forces errors. Rare facts = inevitable guesses. 🔹Post-training: Benchmarks make it worse. Like students gaming exams, models are rewarded for bluffing over admitting uncertainty. Here’s the uncomfortable truth: our evaluation culture drives hallucinations more than the data or architecture. Leaderboards crown smooth guessers, not trustworthy reasoners. 💡The paper’s proposal? Flip the incentives. Change benchmarks so that saying “I don’t know” is rewarded, not punished. That’s how we’ll steer AI toward honesty. Paper: https://lnkd.in/gMrGJDtY 👉 If we keep grading models like test-takers, should we really be surprised when they act like bluffers? Own a piece of agentic AI innovation. GenAI Works is raising capital through our Reg CF campaign. Minimum investment: $1,000 | Class B Common Stock Invest now: https://hubs.li/Q03Hg4gW0 This Reg CF offering is made through DealMaker Securities LLC. Investing involves risk, including loss of principal. #openai #chatgpt #aiethics #hallucinations #artificialintelligence

People are opening up to AI tools more than to parents, friends, even therapists. It feels safe. No judgment. Always available. A blank box that listens. But this trust is fragile and risky. ➡️Studies show humans disclose more personal information to chatbots than to humans when they perceive anonymity (ACM CHI, 2022). ➡️A recent Pew survey found the majority of U.S. adults don’t trust AI to act responsibly, yet paradoxically, usage data shows people pour their most private thoughts into these systems. ⚠️And here’s your warning: your chats aren’t protected like doctor–patient or attorney–client conversations. They can be stored, used to train models, and even disclosed under legal discovery. In 2023, OpenAI had to take ChatGPT offline after a bug exposed other users’ conversation titles. Research has also shown that large language models can memorize and regurgitate snippets of personal data from phone numbers to emails if probed in the right way. Beyond privacy, there’s something deeper👇 1. Emotional dependency on a system that can’t truly care (Nature, 2024 warned about AI “pseudo-relationships”). 2. Replacing human connection with algorithmic conversation is raising concerns among therapists about erosion of real-world vulnerability. 3. Workplace risks: Gartner reported that “shadow AI” (employees pasting confidential data into chatbots) is one of the fastest-growing security blind spots. Are we crossing a line where oversharing with machines changes what intimacy, privacy, and trust even mean? Weekly GenAI walkthroughs, real‑world agent demos and expert insights. Subscribe: https://hubs.li/Q03HdmwW0 Image: u/Benji__-_- #aiethics #privacy #artificialintelligence #machinelearning #chatgpt