--- title: Making robots faster by helping them think ahead | daily.dev description: MIT researchers developed VLASH, a technique that enables vision-language-action (VLA) models to predict a robot's future state while it is still executing... canonical: https://daily.dev/posts/making-robots-faster-by-helping-them-think-ahead-qjfg0ykyj twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Making robots faster by helping them think ahead | daily.dev og:description: MIT researchers developed VLASH, a technique that enables vision-language-action (VLA) models to predict a robot's future state while it is still executing... og:url: https://daily.dev/posts/making-robots-faster-by-helping-them-think-ahead-qjfg0ykyj og:image: https://api.daily.dev/og/posts/qjfg0YkyJ.png og:image:alt: Making robots faster by helping them think ahead og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Making robots faster by helping them think ahead **[MIT News](https://daily.dev/sources/mit)** · 5 min read · 0 upvotes · 0 comments ## Summary MIT researchers developed VLASH, a technique that enables vision-language-action (VLA) models to predict a robot's future state while it is still executing current actions. By planning the next set of motions based on predicted future positions rather than stale current observations, VLASH eliminates the lag between action chunks, achieving over 30x faster reaction speeds. Combined with action quantization — generating coarser, larger action steps — robots complete tasks two to three times faster overall. A training-augmentation method reuses existing data to fine-tune the model fivefold faster with no added computational overhead. In benchmarks, VLASH doubled pick-and-place speed while maintaining 90% accuracy, and also improved performance on dynamic tasks like table tennis and Whack-a-Mole. The approach adds no computational overhead and works across varied robotic hardware. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Vision-Language-Action \(VLA\) Models: From Seeing to Acting with AI Training Data](https://daily.dev/posts/vision-language-action-vla-models-from-seeing-to-acting-with-ai-training-data-cw2kbituu) · Medium · 1 upvotes · 0 comments - [How Visual-Language-Action \(VLA\) Models Work](https://daily.dev/posts/how-visual-language-action-vla-models-work-jln0xmknn) · Towards Data Science · 2 upvotes · 0 comments - [A Comprehensive Overview of Vision-Language-Action Models](https://daily.dev/posts/a-comprehensive-overview-of-vision-language-action-models-3qx6p4llr) · DigitalOcean Community · 1 upvotes · 0 comments --- Tags: [#genai](https://daily.dev/tags/genai), [#robotics](https://daily.dev/tags/robotics) [View this post on daily.dev](https://daily.dev/posts/making-robots-faster-by-helping-them-think-ahead-qjfg0ykyj) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Making robots faster by helping them think ahead","url":"https://daily.dev/posts/making-robots-faster-by-helping-them-think-ahead-qjfg0ykyj","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/making-robots-faster-by-helping-them-think-ahead-qjfg0ykyj"},"datePublished":"2026-07-28T04:02:39.867Z","dateModified":"2026-07-28T04:03:00.169Z","description":"MIT researchers developed VLASH, a technique that enables vision-language-action (VLA) models to predict a robot's future state while it is still executing...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/4f0c3202f9f2d80c684b566a265fe019?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/4f0c3202f9f2d80c684b566a265fe019?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"MIT News","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"MIT News","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/881e20a40aa44b12ba4bd27f5c14289d","url":"https://daily.dev/sources/mit"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/making-robots-faster-by-helping-them-think-ahead-qjfg0ykyj","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"genai,robotics","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"MIT News","item":"https://daily.dev/sources/mit"},{"@type":"ListItem","position":3,"name":"Making robots faster by helping them think ahead"}]} ```