Startups that build artificial intelligence (AI) applications on top of large language models (LLMs) are reportedly making rapid gains in both sales and funding. These startups are reaching as much as $200 million in annual recurring revenue in less than two years and, as a group, increased the amount of funding they attracted by 110% to reach $8.2 billion in 2024, the Financial Times (FT) reported Monday (April 14), citing data from Dealroom.co and Flashpoint. This category of AI startups includes companies like Perplexity, Synthesia,  ElevenLabs, Harvey and Sierra, according to the report

The new OLMoTrace tool builds on the Allen Institute for AI’s open-source initiatives. (Ai2 Image)The Allen Institute for AI (Ai2) released a new tool that links AI-generated text to training data, aiming to improve transparency and accountability in artificial intelligence by addressing one of the biggest mysteries in the field.Ai2 says the project, OLMoTrace, goes further than any other tool to show how the data used to train large language models may influence what they generate.It converts “a black box to a glass box,” said Ali Farhadi, CEO of the Seattle-based nonprofit, during a briefing with reporters at Ai2’s headquarters.OLMoTrace highlights phrases from the AI’s responses that appear verbatim in training data, and links users to the sources. The idea is to support fact-checking and improve understanding of how AI is influenced by training data.The tool, announced Wednesday in conjunction with the Google Cloud Next conference, builds on Ai2’s open approach to AI development, which includes releasing training data, code, model weights, and other components of AI models. Ai2 is making OLMoTrace open-source so others can use, adapt, and build on it.The question of exactly how AI models generate their responses has loomed over AI since the original release of OpenAI’s ChatGPT in November 2022.So what has Ai2 learned from peering into the black box?. VIDEO. While they’ve yet to reach sweeping conclusions, researchers so far have seen examples of AI models repeating patterns the models have seen in training, rather than coming up with answers through reasoning