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AI Suggested 40,000 New Chemical Weapons in Six Hours
From ACM Opinion

AI Suggested 40,000 New Chemical Weapons in Six Hours

Drug-developing artificial intelligence invents 40,000 potentially lethal molecules in quarter of a day.

Deep Learning Is Hitting a Wall
From ACM Opinion

Deep Learning Is Hitting a Wall

What would it take for artificial intelligence to make real progress?

Yoshua Bengio: 'I Have Rarely Been as Enthusiastic about a New Research Direction'
From ACM Opinion

Yoshua Bengio: 'I Have Rarely Been as Enthusiastic about a New Research Direction'

Yoshua Bengio gushes about GFlowNets, calling them "a new beast" for which the appropriate optimization algorithms are still making rapid progress

Security: The Lock and the Key to Blockchain's Future
From ACM Opinion

Security: The Lock and the Key to Blockchain's Future

For blockchain technology to fulfill its full potential, the security standard needs to mature

The Ecological Impacts of Computation and the Cloud
From ACM Opinion

The Ecological Impacts of Computation and the Cloud

The cloud is not only material but also an ecological force

Intelligence and Comprehension
From ACM Opinion

Intelligence and Comprehension

What does it mean to say a computer model 'understands'?

Crypto and Technology for the People
From ACM Opinion

Crypto and Technology for the People

Brown University professor Seny Kamara talks about the intersection between social responsibility and cryptography/technology

Deep Learning Is a Bad Idea for Security
From ACM Opinion

Deep Learning Is a Bad Idea for Security

Deep learning must address some major issues before AI can scale more widely into security applications

Who Gets to Decide if an AI Is Alive?
From ACM Opinion

Who Gets to Decide if an AI Is Alive?

We need a Turing Test for consciousness that works for modern AI

Futures of Digital Governance
From Communications of the ACM

Futures of Digital Governance

Seeking to increase the interoperability among the technical and social sciences toward new forms of governance associated with digital technology.

Copyright Implications of Emulation Programs
From Communications of the ACM

Copyright Implications of Emulation Programs

How emulation programs might be affected by new claims of copyright infringement.

The Metaverse Will Require Computing Tech No One Knows How to Build
From ACM Opinion

The Metaverse Will Require Computing Tech No One Knows How to Build

Experts believe building the metaverse will require nearly every kind of chip to be an order of magnitude more powerful than it is today

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

Tracing the Evolution of the Computer, from Unusual to Ubiquitous
From ACM Opinion

Tracing the Evolution of the Computer, from Unusual to Ubiquitous

New book chronicles computer's journey from scientific instrument to general-purpose device

The Inevitability of Trusted Third Parties
From ACM Opinion

The Inevitability of Trusted Third Parties

The search for a crypto use case continues

The Race to Save the Internet from Quantum Hackers
From ACM Opinion

The Race to Save the Internet from Quantum Hackers

The quantum computer revolution could break encryption, but more-secure algorithms can safeguard privacy

Supercomputing to Save the Planet
From ACM Opinion

Supercomputing to Save the Planet

Fujitsu CTO Vivek Mahajan says true power of cloud will come with democratizing HPC and quantum computers for the masses

Understanding Software Dynamics
From ACM Opinion

Understanding Software Dynamics

In an interview, computer architect Richard L. Sites discusses his new book

Connecting Large Language Models to Human Values
From ACM Opinion

Connecting Large Language Models to Human Values

AI researcher Connor Leahy talks about replicating GPT-2/GPT-3, superhuman AI, AI alignment, AI risk and research norms, and more

Machine-Learning Robustness, Foundation Models, and Reproducibility
From ACM Opinion

Machine-Learning Robustness, Foundation Models, and Reproducibility

An interview with Percy Liang, associate professor of Computer Science at Stanford University
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