August 26, 2024

DeepMind and UC Berkeley shows how to make the most of LLM inference-time compute

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Given the high costs and slow speed of training large language models (LLMs), there is an ongoing discussion about whether spending more compute cycles on inference can help improve the performance of LLMs without the need for retraining them. In a new study, researchers at DeepMind and the University of California, Berkeley explore ways to improve

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Taming the Methodcentipede: Strategies for Writing Simple, Maintainable Code | HackerNoon

When I was a child, I used to lie on the bed and gaze for a long time at the patterns on an old Soviet rug, seeing animals and fantastical figures within them. Now, I more often look at code, but similar images still emerge in my mind. Like on the rug, these images form repetitive patterns. They can be either pleasing or repulsive. Today, I want to tell you about one such unpleasant pattern

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Human Study Validates GPT-4 Win Rates for TL;DR Summarization | HackerNoon

Authors: (1) Rafael Rafailo, Stanford University and Equal contribution; more junior authors listed earlier; (2) Archit Sharma, Stanford University and Equal contribution; more junior authors listed earlier; (3) Eric Mitchel, Stanford University and Equal contribution; more junior authors listed earlier; (4) Stefano Ermon, CZ Biohub; (5) Christopher D. Manning, Stanford University; (6) Chelsea Finn, Stanford University. Table of Links Abstract and 1. Introduction 2 Related Work 3 Preliminaries 4 Direct Preference Optimization 5 Theoretical Analysis

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Robotics

Olis Robotics unveils PLC capabilities for industrial robot cells – The Robot Report

Listen to this article Olis’ PLC system alerts users to what went wrong when a robot stops working. | Source: Olis Robotics End users turn to automation because it promises consistent work with minimal downtime. When something goes wrong, the robot must stop working and wait for a human operator to step in and figure out the problem. During this period, companies are losing out on valuable time and productivity. Olis Robotics said it hopes

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Hardware

PS5 Pro may cost an estimated $600 or $700

Sony’s new PlayStation 5 Pro could cost around $600 or $700 at the higher range, Giant Bomb reporter Jeff Grubb estimates. 2 VIEW GALLERY – 2 IMAGES How much will Sony’s new PS5 Pro be at launch? Given the PS5 Pro’s specs, it could be pricey. The PS5 Pro’s GPU will have 60 RDNA 3.0 Compute Units (CUs) and can boost to a whopping 2.35GHz, which indicates a max 36 TFLOPs of compute power (that’s

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Performance of Best of N Baseline for Various N and Sample Responses and GPT-4 Judgments | HackerNoon

Authors: (1) Rafael Rafailo, Stanford University and Equal contribution; more junior authors listed earlier; (2) Archit Sharma, Stanford University and Equal contribution; more junior authors listed earlier; (3) Eric Mitchel, Stanford University and Equal contribution; more junior authors listed earlier; (4) Stefano Ermon, CZ Biohub; (5) Christopher D. Manning, Stanford University; (6) Chelsea Finn, Stanford University. Table of Links Abstract and 1. Introduction 2 Related Work 3 Preliminaries 4 Direct Preference Optimization 5 Theoretical Analysis

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Software

How Kaizntree Is Becoming the Operations Management Platform for Business Owners Around the World | HackerNoon

Business owners who manufacture their own products encounter several challenges when it comes to managing inventory. This is because their data is often spread across multiple disparate systems that don’t connect to each other — resulting in countless hours of manual data entry and inconsistencies that can cause stock-outs. This is where Kaizntree comes in, an online platform that centralizes the inventory management process by consolidating all data into one interface. It also leverages artificial

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Software

The Unlikelihood Baseline in Sentiment Experiments | HackerNoon

Authors: (1) Rafael Rafailo, Stanford University and Equal contribution; more junior authors listed earlier; (2) Archit Sharma, Stanford University and Equal contribution; more junior authors listed earlier; (3) Eric Mitchel, Stanford University and Equal contribution; more junior authors listed earlier; (4) Stefano Ermon, CZ Biohub; (5) Christopher D. Manning, Stanford University; (6) Chelsea Finn, Stanford University.

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Inflection AI bets on porting Pi chatbot data amid enterprise shift

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Inflection AI, the startup that developed the Pi AI assistant and then witnessed a massive team shuffle following the hiring of its co-founders by Microsoft, is betting on data portability. The company has announced a partnership with the non-profit Data Transfer Initiative (DTI) to help existing Pi users export their data from the platform. While the

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AI

No Baseline? No Benchmarks? No Biggie! An Experimental Approach to Agile Chatbot Development

Lessons learned bringing LLM-based products to production Katherine Munro · Follow Published in Towards Data Science · 12 min read · 6 hours ago — Today’s post recaps my recent talk on lessons learned trying to bring LLM-based products to production. You can check out the video here. What happens when you take a working chatbot that’s already serving thousands of customers a day in four different languages, and try to deliver an even better

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