AI Accelerator Institute
Articles about AI Accelerator Institute
8 AI problems leaders face now, and the fix for each
Eight problems keep landing on AI leaders' desks, and each has a fix backed by fresh data. Start with the two that cost you most this quarter.
Building and optimizing AI agents at scale
When you’re building an AI agent for 70 million users, the stakes are a little different than when you’re prototyping something for a demo. The margin for error shrinks. The edge cases multiply. And the things that feel like minor details in development become very real problems in production
Why enterprise agentic AI needs an evidence standard
Usage metrics show who logged in. Neetu Yadav sets out a five-part evidence standard covering reach, depth of use, quality, risk, and business impact, so enterprise leaders can scale agentic AI with confidence.
Renting GPUs felt smart in 2023: The math has moved
Many enterprise AI initiatives started the same way over the past several years: renting cloud capacity, running pilots, and scaling successful projects. That approach made sense when nobody knew if these use cases would actually hold up in a live production environment
7 reasons small language models belong in your 2027 roadmap
A frontier model reformatting JSON is expensive overkill. Here are seven sourced reasons small language models earn a place in your 2027 roadmap, and how to start.
9 AI predictions for 2027 for your planning deck
Your 2027 planning deck needs sharper assumptions. These nine analyst predictions cover agent governance, power limits, regulation, and physical AI
AIAI Berlin, 2026
Catch up on every session from AIAI Berlin with sessions from Lovable, Aleph Alpha, Bosch and more.
Can you trust your workflow in production?
Moving an agentic workflow out of the pilot stage is where many enterprise AI programs stall. A workflow can look impressive in a demo and still fall short in production, and prompt-level testing alone rarely tells you whether a workflow is truly ready. Agents that answer customer queries, flag suspicious transactions or process claims need to be safe, evidence-based, policy-compliant and appropriately constrained.
Agent washing: 6 questions to vet AI agent vendors
Vendor demos are rehearsed performances. Production is improv night with a hostile crowd. These six questions reveal whether an AI agent can reason, escalate, and hold up on your own messy data before the procurement paperwork lands.
Barndoor Live Workshop
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Bridging the gap from supercomputing to AI factories
An on-demand webinar on how enterprises are modernizing HPC for the AI era, with insights from NVIDIA and WEKA leaders
Why your AI fails in production
Your roadmap says production. Your pilot says otherwise. Inference demand is climbing. Agentic workflows are getting more complex. Your stack now has three models doing the job one used to. Meanwhile the budget holders want proof it's all paying off. In this live working session, Nebius product leaders open up the full system behind production AI, from compute and data infrastructure to model serving and continuous improvement. They'll show where it breaks and what it takes to turn ambition into outcomes you can defend.
Why AI Containment Stalls at 60% and How to Reach 85%
Let me explain what I mean. At Omilia, we've been building AI solutions for 23 years. Long before "generative AI" became a dinner table conversation, long before every company started slapping ".AI" on their name and calling themselves a tech company. (I read an article recently about a shoe company that gave up on shoes entirely to rebrand as an AI company. I'm still not sure what to make of that.) The point is, AI has been around and doing real work for a long time.
AI prompts: what separates AI leaders from hobbyists
Three in four board members rate their AI knowledge highly, and their CEOs disagree. The gap shows up in a single prompt, and the fix takes about 30 seconds of extra typing
What agentic AI will look like in 2030
Builders shipping agentic AI right now describe 2030 as delegation with receipts, not the runaway autonomy the keynotes promise. Here is what memory, governance, and the workforce math actually look like once the hype settles.