Run LLM Agents as Microservices with One-Click Deployment

https://agentainer.io/

“When implementing an AI strategy, #companies have to look at all these aspects to find the best fit for their needs. This is harder than it sounds. A business’s decision on how to #deploy AI is very different to choosing a static #technology stack to be rolled out across an entire organisation in an identical way.

Businesses have yet to understand that a successful #AIStrategy is “no longer a #tech decision made in a tech department about #hardware”, says #MackenzieHowe, co-founder of #Atheni, an AI strategy #consultant. As a result, she says, nearly *three-quarters of #AI rollouts do not give any return on investment*.”

#WhiteCollar / #ZeroHourWork / #infrastructure / #AIDeployment <https://www.ft.com/content/8452bf94-9a41-4040-913f-ef1a462d6ea6> (paywall) / <https://archive.md/WlhLh>

AI adoption matures, but big challenges remain

68% of companies now run custom AI in production, with 81% spending $1M+ annually. But issues like poor data, tough training, and project delays still slow progress. As AI goes mainstream, control and trust are the next big frontiers.

#ArtificialIntelligence #AIDeployment #EnterpriseAI #DataQuality #MachineLearning #GenerativeAI

https://www.artificialintelligence-news.com/news/ai-adoption-matures-deployment-hurdles-remain/

Google AI Edge – on-device cross-platform AI deployment

https://ai.google.dev/edge