When artificial intelligence systems began acing long-standing academic assessments, researchers realized they had a problem: the tests were too easy. Popular evaluations, such as the Massive Multitask Language Understanding (MMLU) exam, once considered formidable, are no longer challenging enough to meaningfully test advanced AI systems.
HD version is here since Reddit downscaled massively : https://youtube.com/shorts/WgGN2fqIPzo submitted by /u/CeFurkan [link] [comments]
Using large language models (LLMs) — or their outputs, for that matter — for all kinds of machine learning-driven tasks, including predictive ones that were already being solved long before language models emerged, has become something of a trend.
Large-scale commercial search systems optimize for relevance to drive successful sessions that help users find what they are looking for. To maximize relevance, we leverage two complementary objectives: behavioral relevance (results users tend to click or download) and textual relevance (a result’s semantic fit to the query). A persistent challenge is the scarcity of expert-provided …
Read more “Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments”
Prompt: upscale image and remove jpeg compression artifacts. Added few hours later: Please note that nowhere in the text of the post did I say that it works well. The comparison simply shows the current level of this model without LoRAs and with the most basic possible prompt. Nothing more. submitted by /u/CutLongjumping8 [link] [comments]
Language models generate text one token at a time, reprocessing the entire sequence at each step.
There’s a lot of excitement right now about AI enabling mainframe application modernization. Boards are paying attention. CIOs are getting asked for a plan. AI is a genuine accelerator for COBOL modernization but to get results, AI needs additional context that source code alone can’t provide.Here’s what we’ve learned working with 400+ enterprise customers: mainframe …
Read more “Learnings from COBOL modernization in the real world”
With the dawn of the gen AI era, businesses are facing unprecedented opportunities for transformative products, demanding a strategic shift in their technology infrastructure. A few years ago, PayPal, a digital-native company serving hundreds of millions of customers, faced a significant challenge. After 25 years of success in expanding services and capabilities, we’d created complexity …
Read more “PayPal’s historically large data migration is the foundation for its gen AI innovation”
A new bill that would give farmers in Iowa the right to repair is a big threat to tractor manufacturer John Deere.
Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming and multistep planning. But developing reasoning models demands an enormous amount of computation and energy due to inefficiencies in the training process. …
Read more “Adaptive drafter model uses downtime to double LLM training speed”