The competition between the US and China has sparked intense advances in AI that will be impossible to stop anywhere. The change will be massive, and not all of it good. As my Uber driver in Cambridge has already intuited, AI will displace a large number of jobs, which will cause social discontent. Consider the progress of Google DeepMind's AlphaGo software, which beat the best human players of the board game Go in early 2016. It was subsequently bested by AlphaGo Zero, introduced in 2017, which learned by playing games against itself and within 40 days was superior to all the earlier versions.

Breakthroughs in technology are typically attributed to a single lone genius, but research led by DeepMind scientist Thore Graepel suggests the full power of AI will be unleashed through a collective approach of multi-agents. The UCL machine learning professor helped create AlphaGo, which pursued an individual strategy called competitive self-play to become the first computer program to defeat a human professional Go player in 2015. He's since turned his focus from competition to cooperation, using deep reinforcement learning to understand how teamwork develops among self-interested agents, whether they're computer programmes or human social dilemmas. "We believe that this kind of model is a powerful baseline to study these kinds of social dilemmas in more detail," said Graepel at the AI for Social Good symposium at the Turing Institute. His work forms part of DeepMind's ambitious mission "to solve intelligence".

Hi all, quick question - is the Deep Learning component only enabled for endpoints and not servers as it can be disabled in endpoint policies but there's no mention of it in any server policies.

In a recent blog, I discussed Intel's work with Thorn, an organization that leverages technology to fight child sex trafficking. Intel and Thorn use machine learning to match online images of children in sexually explicit content with images of known missing children. With the power of artificial intelligence (AI), we hope to accelerate victim identification, disrupt the platforms that host this content and deter predators. This is an excellent example of how technology can be an important weapon in the fight to protect children. Intel's work with Thorn combines artificial intelligence and machine vision to help solve business and societal challenges.

"For many decades hype outstripped fact in terms of AI and machine learning. "This report looks at the practices that just don't work anymore and suggests broad approaches that might help: for example, how to design software and hardware to make it less hackable - and what type of laws and international regulations might work in tandem with this." The report urges policy makers and researchers to work together to understand and prepare for how the technology could be used maliciously, and calls for developers to be proactive and mindful of how it could be misused. Those who contributed to the study include the Elon Musk-founded non-profit research firm OpenAI and international digital rights group the Electronic Frontier Foundation.

Abstract: The design of small molecules with bespoke properties is of central importance to drug discovery. However significant challenges yet remain for computational methods, despite recent advances such as deep recurrent networks and reinforcement learning strategies for sequence generation, and it can be difficult to compare results across different works. This work proposes 19 benchmarks selected by subject experts, expands smaller datasets previously used to approximately 1.1 million training molecules, and explores how to apply new reinforcement learning techniques effectively for molecular design. The benchmarks here, built as OpenAI Gym environments, will be open-sourced to encourage innovation in molecular design algorithms and to enable usage by those without a background in chemistry. Finally, this work explores recent development in reinforcement-learning methods with excellent sample complexity (the A2C and PPO algorithms) and investigates their behavior in molecular generation, demonstrating significant performance gains compared to standard reinforcement learning techniques.

Machine learning in production happens in five phases. Most machine-learning systems are ad hoc.) Within each phase, we'll explain: Goal Identify a data-intensive business problem and propose a potential machine learning solution. Goal Rapidly explore and de-risk a use case before significant engineering resources are dedicated to it, make "go/no go" recommendation Overlaps with Phase 3 (model training) except here we don't expect a fully tuned model, nor do we expect to produce a reusable software artifact. NOTES: Overlaps with Phase 2 (feasibility study), but here we expect a fully tuned model and a reusable software artifact.

In a new report, called The Malicious Use of Artificial Intelligence (AI), the authors - who are made up of AI researchers and civil liberties groups - warn that if breakthroughs in AI continue at the current pace then technology will soon become so powerful that it will outmanoeuvre many digital and physical defence systems. Jack Clark, head of policy at OpenAI, San Francisco-based AI group whose backers include Elon Musk and Peter Thiel, said: "What struck a lot of us was the amount that happened in the last five years -- if that continues, you see the chance of creating really dangerous things." The report also warns that drones and driverless cars could be commandeered and used as weapons and that malevolent AI could be used to organise swarms of drones. Also, political systems could be hacked by using tools for online advertising and commerce to manipulate voters.

I will show you how to use Google Colab, Google's free cloud service for AI developers. With Colab, you can develop deep learning applications on the GPU for free. Google Colab is a free cloud service and now it supports free GPU! The most important feature that distinguishes Colab from other free cloud services is: Colab provides GPU and is totally free. Detailed information about the service can be found on the faq page. Since Colab is working on your own Google Drive, we first need to specify the folder we'll work.

PARIS – Artificial intelligence could be deployed by dictators, criminals and terrorists to manipulate elections and use drones in terrorist attacks, more than two dozen experts said Wednesday as they sounded the alarm over misuse of the technology. In a 100-page analysis, they outlined a rapid growth in cybercrime and the use of "bots" to interfere with news gathering and penetrate social media among a host of plausible scenarios in the next five to 10 years. "Our report focuses on ways in which people could do deliberate harm with AI," said Sean O hEigeartaigh, Executive Director of the Cambridge Centre for the Study of Existential Risk. "AI may pose new threats, or change the nature of existing threats, across cyber, physical and political security," he said. The common practice, for example, of "phishing" -- sending emails seeded with malware or designed to finagle valuable personal data -- could become far more dangerous, the report detailed.