Natural Language Processing (NLP)

5 Posts

AYA Vision architecture diagram showing vision encoder, multimodal merging, and LLM backbone for image processing
Natural Language Processing (NLP)

Equally Fluent in Many Languages: Cohere’s Aya Vision beats multilingual rivals in text & image understanding

Multilingual AI models often suffer uneven performance across languages, especially in multimodal tasks. A pair of lean models counters this trend with consistent understanding of text and images across major languages.
Amazon smart display with widgets for recipes, calendar, weather, events, and streaming (Prime Video, Netflix, Disney+).
Natural Language Processing (NLP)

Amazon’s Next-Gen Voice Assistant: Alexa+ adds generative AI and agents, using Claude and other models

Amazon announced Alexa+, a major upgrade to its long-running voice assistant.
A participant types while an MEG scan decodes brain activity into text in real-time, showing typed vs. decoded text.
Natural Language Processing (NLP)

Reading Minds, No Brain Implant Required: Brain2Qwerty, a system that decodes thoughts using brain waves without surgery

To date, efforts to decode what people are thinking from their brain waves often relied on electrodes implanted in the cortex. New work used devices outside the head to pick up brain signals that enabled an AI system, as a subject typed, to accurately guess what they were typing.
Diagram showing GPT-4o with and without search, highlighting task execution success and failure.
Natural Language Processing (NLP)

Tree Search for Web Agents: How tree search improves AI agents’ ability to browse the web and complete tasks

Browsing the web to achieve a specific goal can be challenging for agents based on large language models and even for vision-language models that can process onscreen images of a browser.
Bar chart comparing active vs. random sampling effects on length, diversity, and toxicity after fine-tuning.
Natural Language Processing (NLP)

Fine-Tuning Fine Points: Active inheritance, a smarter way to fine-tune models on synthetic data

The practice of fine-tuning models on synthetic data is becoming well established. But synthetic training data, even if it represents the training task well, may include characteristics like toxicity that impart unwelcome properties in the trained model’s output...

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