In most of the last 10 years, Machine Learning (ML) was the heaviness of the concept embedding: An ML model would learn how to convert input data to vectors (embedders) so that geometric conditions within the vector room had semantic consequences. For example, words whose embeddies were close to each other in the representative space … Read more
As the start of this year’s Interspeesch is approaching, “Generative AI” has become a guard word in both the machine learning community and the popular press, where it generally refers to models that synthesize text or images. TTS) Models (TTS-to-Tale), which is an important research area at Interspeech, has in some sense always been “generative”. … Read more
The drive to exploit the transformative power of high-end machine learning models has meant that some businesses are facing new challenges. Team wants help preparing complete documents, summarizing complex documents, conversation-IA agents who build or generate striking, customized visuals. In April, Amazon stepped in to help clients fight with the need to build and scale … Read more
USC + Amazon Center on secure and trusted machine learning,,,,,,,, Established in January 2021 to support basic research and development of new approaches to Machine Learning (ML) Privacy, Security and Reliability, announced today that it has chosen six research projects for 2023-2024, including oven facial projects and two academic projects by new Amazon ML fellowships. … Read more
Today’s major machine learning models-as generative language models or vision-language models, are so great that the process of educating them is typically divided across thousands or even tens of thousands of GPUs. Even with all that parallelism, training still often takes months. With such a massive implementation of resources, hardware and software errors are common … Read more
When a large language model (LLM) is quick with a request such as Which medications are likely to interact with St. John’s Wort?It does not seek a medically validated list of drug interactions (unless it has been trained to do so). Instead, it generates a list based on the distribution of words associated with St. … Read more
Last month, at its annual RE: Invent Development ‘Conference, Amazon Web Services (AWS) announced the release of two new additions to its Titan Family of Foundation models, both of which translate between text and images. Related content AWS SERVICE Enable Machine Learning Innovation at Robust Foundation. With Amazon Titan Multimodal embedders now available via Amazon … Read more
For all their remacable abilies, large language models (LLMs) have an Achilles heel, which is their tendency to hallucinate or make claims that sound plausible but invoice inaccurate. Sometimes these hallucinations can be subtle: An LLM can, for example, make a claim that is most accurate, but gets a date wrong with only one year … Read more
For centuries, theories of meaning have been almost exclusively interested in philosopher, discussed in seminar rooms and at conferences for small special audiences. But the emergence of large language models (LLMs) and other “Foundation Models” have changed it. Suddenly, mainstream media live with speculation about what is only trained to predict the next word in … Read more
Autoomous Vehicles (AVS) such as Zoox-Special-built Robotaxi take a new era in human mobility, but the implementation of AVS comes with many challenges. It is important to perform extensive safety test simulation, which requires the creation of synthetic driving scenarios on scale. Particularly important is to generate realistic safety -critical road scenarios, to test how … Read more