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dateMore Than a Year Ago
subjectComputer Systems
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How to Solve AI's 'Common-Sense' Problem
From ACM Opinion

How to Solve AI's 'Common-Sense' Problem

AI systems without common sense will make mistakes when they reach the limits of where they've been trained.

Democratizing LLMs Needs a Revolution in AI Hardware
From ACM Opinion

Democratizing LLMs Needs a Revolution in AI Hardware

Hardware barriers must be overcome to make LLMs available to a broader audience.

'Sentience' Is the Wrong Discussion to Have on AI Right Now
From ACM Opinion

'Sentience' Is the Wrong Discussion to Have on AI Right Now

A more important conversation would be one about human compatibility and trust.

Can Large Language Models Be Democratized?
From ACM Opinion

Can Large Language Models Be Democratized?

The very nature of large language models is undemocratic and in favor of the companies that publicize them.

The AI in a Jar
From ACM Opinion

The AI in a Jar

Exploring a metaphysical argument against artificial intelligence.

Democratize Machine Learning with No-Code AI
From ACM Opinion

Democratize Machine Learning with No-Code AI

Organizations lacking skilled data scientists and ML engineers can create and deploy ML models, too.

Humans and AI: Problem Finders and Problem Solvers
From ACM Opinion

Humans and AI: Problem Finders and Problem Solvers

Technologies such as AlphaCode cannot think about and design their own problems, but they are very good problem solvers

Individual AI, a New Technology that Will Change Our World?
From ACM Opinion

Individual AI, a New Technology that Will Change Our World?

Is the next version of AI a technological symbiosis of the human brain and the computer system?

Does AI Understand Our Language?
From ACM Opinion

Does AI Understand Our Language?

Can large language models teach us about the nature of language, understanding, intelligence, sociality, and personhood?

Why We Must Rethink AI Benchmarks
From ACM Opinion

Why We Must Rethink AI Benchmarks

While helpful in comparing AI performance, benchmarks are often taken out of context, sometimes to harmful results

Why Machine Learning Can't Understand Human Language
From ACM Opinion

Why Machine Learning Can't Understand Human Language

While larger deep neural networks can incrementally improveme specific tasks, they aren't fit for general natural language understanding.

Building Artificial Intelligence: Reward Is Not Enough
From ACM Opinion

Building Artificial Intelligence: Reward Is Not Enough

Rewards are not enough to build artificial intelligence, says data scientist Herbert Roitblat, countering claims from a recent paper by DeepMind scientists.

Tesla AI Chief Says Self-Driving Cars Don't Need Lidar
From ACM Opinion

Tesla AI Chief Says Self-Driving Cars Don't Need Lidar

Andrej Karpathy shares why the company still believes in a purely vision-based autonomous driving solution.

Machine Learning Security Needs New Perspectives and Incentives
From ACM Opinion

Machine Learning Security Needs New Perspectives and Incentives

Researchers and developers racing to make deep learning available to different applications need to actively seek out and address security challenges before they...

Understanding the Differences Between Biological and Computer Vision
From ACM Opinion

Understanding the Differences Between Biological and Computer Vision

Harvard Medical University Professor Gabriel Kreiman provides an account of how humans and animals process visual data and how far techno come toward replicating...
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