Tools vs. Subagents: Building Effective AI Agents Without Over-Engineering
Tools execute code.
Intelligence is Free, Now What? Data Systems for, of, and by Agents
… government of the people, by the people, for the people … — Abraham Lincoln, Gettysburg Address (1863) The cost of AI is dropping rapidly. GPT-4-class capabilities cost roughly $30 per million tokens in early 2023; today the same runs under $1, and some providers are pushing costs below $0.10. Across benchmarks, inference prices have …
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Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction
This study focuses on Text-to-Sounding-Video (T2SV) generation, which aims to generate a video with synchronized audio from text, with both modalities aligned to the text conditions. Despite progress in joint audio-video training, two critical challenges remain: (1) text conditioning is a bottleneck—shared captions (TV=TA) trigger modal interference, while a gap persists between dense training captions …
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Enrich your datasets with business context: Migrating from legacy Topics to semantic datasets in Amazon Quick
If you’ve been managing Amazon Quick legacy Topics alongside your datasets, you know the challenge: two assets that must stay perfectly synchronized, each with its own permissions, lineage, and versioning. Column synonyms drift. Calculated fields diverge. A rename in the dataset breaks the Legacy Topic silently. You can now use Amazon Quick to embed that …
A developer’s guide to publishing agents in Gemini Enterprise and Google Cloud Marketplace
Software-as-a-service (SaaS) is evolving into Agents-as-a-service (AaaS). Instead of isolated applications, developers are creating AI agents that interoperate using standardized open protocols such as the Agent2Agent (A2A) protocol and can be orchestrated through centralized agent platforms like Gemini Enterprise Agent Platform. When building for your specific use case, we believe the goal should always be …
Meta Now Lets Anyone Use Your Instagram Photos in AI Images—Unless You Opt Out
As part of Meta’s Muse Image model rollout, Instagram users with public accounts need to opt out to block AI generations of their content.
Automation system advances efficient AI workflows
Your online order arrives damaged, so you request a refund. What often follows is an artificial intelligence workflow involving multiple AI models: One model checks your request against company policy, another analyzes the image you uploaded, and yet another drafts a response.
The Complete Guide to Tool Selection in AI Agents
You build an agent with five tools.
Revisiting ASR Error Correction with Specialized Models
Language models play a central role in automatic speech recognition (ASR), yet most methods rely on text-only models unaware of ASR error patterns. Recently, large language models (LLMs) have been applied to ASR correction, but introduce latency and hallucination concerns. We revisit ASR error correction with compact seq2seq models, trained on ASR errors from real …
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From Hugging Face to Amazon SageMaker Studio in one click
Today, we’re excited to announce a deep-link integration between Hugging Face and Amazon SageMaker AI. Developers can now go from model discovery to hands-on experimentation in SageMaker Studio with a single selection. Whether you fine-tune a foundation model (FM) from Amazon SageMaker JumpStart or deploy it to an Amazon SageMaker Inference endpoint, you can now …
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