Artificial intelligence could transform the public sector, but adoption has been slow. As the Government Office for Science publishes its report into the subject, Richard Sargent, director of ASI and former performance lead at the Government Digital Service, says leadership and culture will be crucial for success.
With a new set of principles for artificial intelligence, tech pioneers seem to be developing a conscience. Good – but the discussion must include more voices
We all like to believe we are rational human beings, and can understand the power of machine learning, just as we understand the simple logic of an A/B test. But how will company cultures react to machines that could be seen to undermine your star copywriter or best biz dev guy?
Christopher S Penn looks at how to plan and build our first machine learning/AI project with the AI/Machine Learning Lifecycle. Complicated post, but could be useful.
Thanks to advances in technology, many jobs that weren’t considered ripe for automation suddenly are
Artificial intelligence and machine learning will create computers so sophisticated and godlike that humans will need to implant “neural laces” in their brains to keep up, Tesla Motors and SpaceX CEO Elon Musk told a crowd of tech leaders this week (June 2016).
In the grandest irony of all, the greatest benefit of an everyday, utilitarian AI will not be increased productivity or an economics of abundance or a new way of doing science—although all those will happen. The greatest benefit of the arrival of artificial intelligence is that AIs will help define humanity. We need AIs to tell us who we are.
AI researchers know that neural networks are still quite flawed, so much so that some wonder whether these pattern recognition systems are a viable path to more advanced—and more reliable—forms of AI.
Artificial Intelligence and Journalism
Algorithms seem certain to play a growing role in the production and curation of news, but it remains unclear what exactly this trend will mean for journalism — or for the human journalists who currently produce it.
Research by Oxford University has predicted that journalism is among the jobs least likely to be replaced by a machine in the near future. And yet, as Columbia University prepares to celebrate 100 years of the Pulitzer prize, intelligent robots will publish financial reports, sports commentaries, clickbait and myriad other articles formerly the preserve of trained journalists.
When it gets to the point that a computer can consistently generate content at a level that passes the Turing Test, the economics of content in every form will change forever. Essentially, computers work for free, all day, without breaks, illness, or vacation time. What company will not want that? Mark Schaefer asks: “Us there any way to future-proof ourselves from automated writing, or will we soon merely remember our days of human writing with nostalgia?”
Sites like the New York Times, the Washington Post, CNN, and NBC are using artificially intelligence systems to cover the 2016 elections in the United States.
Artificial Intelligence and Health
In hopes of creating better access to medical care, Stanford researchers have trained an algorithm to diagnose skin cancer.
DeepMind cofounder Mustafa Suleyman gave a rare insight into the work he and his team are doing within Google during a machine learning conference in London in June 2015.
A project by the University of Oxford and UK-based DeepMind, owned by Google parent company Alphabet, trained an artificial-intelligence system to read lips by analyzing 5,000 hours of TV programs, reported New Scientist on Monday.
DeepMind is now capable of teaching itself based on information it already possesses. In a significant step forward for artificial intelligence, Alphabet’s hybrid system — called a Differential Neural Computer (DNC) — uses the existing data storage capacity of conventional computers while pairing it with smart AI and a neural net capable of quickly parsing it.
Google’s DeepMind artificial intelligence has produced what could be some of the most realistic-sounding machine speech yet. WaveNet, as the system is called, generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio.
Artificial intelligence is getting its teeth into lip reading. A project by Google’s DeepMind and the University of Oxford applied deep learning to a huge data set of BBC programmes to create a lip-reading system that leaves professionals in the dust.
Other case studies:
- Watch Google’s AI master the infamously difficult Atari game Montezuma’s Revenge
- Google Cuts Its Giant Electricity Bill With DeepMind-Powered AI
Facebook and AI
That’s the basic principle of why Deep Learning (DL) is useful to Facebook, and as DL algorithms become more sophisticated they can increasingly be applied to more data that we share, from text to pictures to videos. So here’s a couple of specific use cases where DL is used to gain value and help Facebook achieve its goals of providing greater convenience to users, and enabling them to learn more about us.
For many working in artificial intelligence, the ultimate goal is a general AI: software that could reason its way through any problem, like a human but on a superhuman scale. Humans are only now realizing how to make an AI proficient at simple tasks, like identifying objects in photos, which means an actual general AI is still a pipe dream. That hasn’t stopped a handful of researchers at Facebook from toying with how a general AI would work, and how we might measure progress in building one, if such a thing could be built.
Initially used to improve the experience for visually impaired members of the Facebook community, the company’s Lumos computer vision platform is now powering image content search for all users. This means you can now search for images on Facebook with key words that describe the contents of a photo, rather than being limited by tags and captions.
If we’re going to move toward generalized intelligence, Facebook wants to make sure we know how to evaluate progress. In a paper, Facebook’s AI Research (FAIR) lab outlines just that as part of its CommAI framework.