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Our unrealistic expectations of genAI are like hoping a two-year-old will calmly act like an adult. Try patiently experimenting with prompts and spending ‘quality time’ with this developing technology.
Cloud and AI are the most important technologies today, and both have outstripped open source licenses. It’s time for a new open source definition.
10 quirks, consequences, and questions from an amazing and unsettling year of dizzying AI advances.
As the big vendors overstate the capabilities of their generative AI projects, maybe it’s time to use open source to keep them honest.
The new program allows researchers to cut through waiting queues or wait times while providing the option to connect with experts to seek guidance on quantum workloads.
The high costs of development and training and the lack of pricing transparency put commercial large language models out of reach for many companies. Open source models could change that.
Billionaires’ promises of a utopian AI future aren’t helping us solve the serious problems with today’s generative AI models. Security is top of the list.
Large language models trained on questionable stuff online will produce more of the same. Retrieval augmented generation is one way to get closer to truth.
Forty years ago, AI was largely shelved because of its high price tag. By finding the real business benefits, you can do better than the developers of yesterday.
There’s a lot of talk but not many actual implementations of generative AI in the cloud. Better to have all the pieces in place before launching expensive projects.