AWS broken Generative AI Strategy

First, let’s talk about Bedrock, their AI service managed API. It’s been delayed for quite a while and doesn’t seem ready for prime time. They have their own models like Titan and also incorporate third-party models, but the current state of Bedrock is disappointing. It’s still being trained, and there are no benchmarks available to gauge its performance. By the time it’s released, Google’s Gemini and OpenAI’s Multimodal capabilities will likely be on the scene, making Bedrock seem subpar in comparison. AWS is losing ground by being slow to innovate and struggling to catch up with innovations that happened almost a year ago. It’s disheartening to see AWS, known for being a premium cloud provider, lagging behind its competitors. Moving on to the HuggingFace partnership, it seems to be facing its own set of issues. The models they offer through SageMaker JumpStart are outdated and don’t perform well in terms of throughput or latency. Tuning jobs frequently fail, and the support for newer models is unreliable. While the collaboration with HuggingFace is meant to bring optimized container images for DIY inference with open-source models, many users find it complex and frustrating to work with. It’s disappointing to see that what was promised as a valuable partnership has turned into a broken experience. The whole strategy and direction seem to be failing, lacking focus and gasping for fresh outlook. TC: 370k 🥜 now