The question isn't whether new jobs emerge. It's who captures the upside and who bears the cost. That's not a messaging problem. It's a power structure problem.

How is anyone in the U.S. — who is not working at a handful of AI companies and who is not independently wealthy — paying their bills right now?

The correct way to handle AI cyber security: No guardrails.

Technology hysteria through the ages: trains will drive you mad, the atmosphere will ignite, grey goo will consume us. Calling everything FUD is easy. Telling genuine structural questions from mere panic is rather harder.

How to master Claude - 10x your AI productivity with this playbook.👇 (as a complete beginner)

A well regulated AI, being necessary to the security of a free State, the right of the government to suspend any model for any reason shall not be questioned.

If you follow people covering payments, tokenization via blockchain & they haven't covered this doc, well, either they aren't paying attention or don't want you to know. @IOV_OWL & I both shared the gem. It's time to stop speculating and get the facts. This is when DYOR matters. icmagroup.org/assets/documen…

#Data debt >> AI’s #value killer hidden in plain sight buff.ly/pnAbPIV #tech #digital #innovation #disruption #leadership #business #management #governance #CIO #CTO #CDO #CEO #strategy #AIStrategy #digitalstrategy #digitaltransformation #technicaldebt @Forbes @BobViolino @BetaMoroney @ChuckDBrooks @MikeFlache @Khulood_Almani @IngridVasiliu @JonBelsher @Timothy_Hughes @NafisAlam @YuHelenYu @RLDI_Lamy @MCLynd @OlKonol_oa @RigneySec @BenRothke @HWillert @AndrewinContact @TerenceLeungSF @Shi4Tech @enilev @Nicochan33 @SabineVdL @bimedotcom @IanLJones98 @FrRonconi @RiccardoBua @Eli_Krumova @NYIke @HaroldSinnott @SallyEaves @GlobalIQX @AntGrasso @AkwyZ @DinisGuarda @PVynckier @YvesMulkers @HaleChris @BillMew @RobMay70 @NigelTozer @m49D4ch3lly @Ronald_vanLoon @jeancayeux @NevilleGaunt @asokan_telecom @cybersecboardrm @RVP @QuePasaChico

By the very nature of such restrictions, one does not prevent capability. One merely relocates it. Those who build walls around knowledge always assume the world outside stands still. It does not.

🐍📰 Why You Should Attend a Python Conference Attending a Python conference can grow your network, skills, and confidence. Follow this guide to take your first steps toward joining a Python event #python realpython.com/python-confer…

Storage is the quiet crisis in large-scale compute. QLC for read-heavy workloads is sensible. But efficiency gains in service of an inefficient architecture is not progress. It is merely optimization.

At Box, we just surveyed 1,640 IT leaders across the US, Japan, and Europe about agentic AI adoption. Many standout findings, but a big one was that the companies that adopted AI the most are planning to grow headcount the most. Obviously lots of ways you can read that data and variables mixed in, but it’s actually quite intuitive that the companies that become most productive want to (and are able to) reinvest back into the business to keep getting the gains going. The narrative of jobs being wiped out assumes that companies will take a fixed approach to what they want to be able for work on. What’s happening in practice is it’s causing companies to want to light up more engineering projects, sell to more customers, automate more processes to give time back, and more. That all leads to more work to be done by people.

⚡ Google DeepMind just dropped DiffusionGemma, latest experimental open model (Apache 2.0) that generates text up to 4x faster. - Uses diffusion instead of traditional next token autoregressive generation - Generates and refines 256 token blocks in parallel - Achieves up to 700 tokens/sec on RTX 5090 and 1000 tokens/sec on a single H100 - Designed as a 26B MoE model but activates only 3.8B params during inference - Can run quantized within 18 GB VRAM - Supports bidirectional attention during generation - Can self correct outputs during inference through iterative denoising - Handles global context much better than standard left to right models - Particularly strong for constraint based tasks like Sudoku - Fine tuned Sudoku version reached 80% success while base model was near 0% - Uses block autoregressive diffusion for long context generation - Integrated directly into vLLM for OpenAI compatible serving - Released with official training recipes and fine tuning support - Optimized across RTX 4090, RTX 5090, Hopper, and Blackwell GPUs Getting started: - Model weights are available publicly on Hugging Face - Works with vLLM, Hugging Face Transformers, and MLX - Deployable through Google Cloud Model Garden and NVIDIA NIM - Google released official fine tuning recipes through Hackable Diffusion License: - Released under Apache 2.0 - Allows commercial usage - Allows modification and redistribution - Developers can fine tune and build products on top of it This is one of the strongest public signs yet that major labs are actively exploring post autoregressive architectures for future LLMs.

Forget AGI, This is a great demo to show how much education can be transformed with LLMs! Education is the cornerstone of any civilization and rightly done, LLMs and generative Media can unlock newer ways of doing it. Imagine Khan Academy but bolstered withe modern AI! 🔥

Technology hysteria update: the AGI already decided you're underclass before you pressed enter. But the quieter truth is AI amplifies existing power structures by default. Not conspiracy, just consolidation.

It is crazy to see how tech has evolved over time. If you were active online before the ChatGPT era, you might remember that every blog, conference, newsletter, YouTube video, book, meetup, tweet used to be about React, Next.js, Angular, Tailwind, Node.js, etc. Now, almost everything is about Codex, Claude Code, LLMs, agents, and AI workflows. I sometimes miss old school tech content.

I keep saying: emergent behavior needs guardrails, not micromanagement. 44 agents proved it-11x throughput, hard constraints, zero chaos.

Now your Hermes Agent has an easy GUI based way to build and design your agent profiles to curate the perfect setup for every task and need! `hermes update` and load into your Dashboard, and start building custom agents today!

Six appointees and quarterly meetings. Where mature, common law regulatory infrastructure exists from day one, these friction cycles simply don't occur. It is architectural.

Cheaper models require different architectures. These are not those architectures.