Just what i find

In a scary development, China expects to deploy AI powered submarines capable of executing weapon strikes on targets within the next 2-3 years. https://www.artificialintelligence-news.com/2018/07/23/china-sea-power-unmanned-ai-submarines/ China is planning to upgrade its naval power with unmanned AI submarines that aim to provide an edge over the fleets of their global counterparts. Continue reading →

Although some are pitching it as "replacing" human call centre workers, a more likely scenario is that mundane or routine interactions can be completely automated, allowing human workers to spend more time on more meaningful, complex or sensitive activities. Yes, this will probably lead to individual call centres hiring fewer people, it could well pan out the same way as ATMs (http://www.aei.org/publication/what-atms-bank-tellers-rise-robots-and-jobs/) – it made the cost of banking cheaper, meaning banks could extend their reach further and open more branches. https://bgr.com/2018/07/24/google-ai-call-centers-focus-of-software/ This is the second time in a matter of just a few weeks we’re back writing about how… Continue reading →

Planning how to deploy people and resources (like water and fertiliser) to make the best use of yield is critical to optimising costs in highly volatile industries like wine making. Using drones to survey vineyards (which takes just 15 minutes), and analysing the results using AI, produces faster and more accurate results – the system can even identify grapes which have been too close to bushfires (which would taint the wine with a smokey taste), and can predict with high accuracy when grapes are at their optimal time for harvesting, ensuring that the exact ratio of sugars, mature and just… Continue reading →

Although (in theory) any randomly scrambled Rubik's Cube can be solved in 20-26 moves, current solutions are basically based on brute force searches. Given the massive number of combinations (4.3 × 10^19), one major challenge to training a system is the sparse reward mechanism – DeepMind's paper outlines the use of a new algorithm – "Autodidactic Iteration" – using 2,000,000 iterations over approximately 8 billion cubes in just 44 hours. https://www.hpcwire.com/2018/07/25/new-deep-learning-algorithm-solves-rubiks-cube/ Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and Continue reading →

Driving increased "data gravity" means customers are less likely to divert new data workloads to alternative platforms, and SalesForce's two recent acquisitions – MuleSoft (a data integration and transformation company) for $6.5 billion in March (https://www.fool.com/investing/2018/03/23/salesforcecom-makes-a-transformative-move-for-the.aspx) and Datorama (cloud AI for marketing) for $800 million (https://www.fool.com/investing/2018/07/27/salesforce-strengthens-its-ai-capabilities-with-an.aspx) further highlight their desire to make it as easy as possible for customers to get data on to their platform and process it there. https://www.fool.com/investing/2018/07/27/salesforce-strengthens-its-ai-capabilities-with-an.aspx The relationship management software company has announced its fourth acquisition this year. Continue reading →

Recent advances in AI mean that it would now be possible to develop autonomous weapons – systems which are capable of making automated decisions to take human life. Elon Musk, DeepMind and others have signed a pledge never to create AI weapons: "We the undersigned agree that the decision to take a human life should never be delegated to a machine. It goes on to warn "lethal autonomous weapons, selecting and engaging targets without human intervention, would be dangerously destabilizing for every country and individual." https://www.forbes.com/sites/samshead/2018/07/18/elon-musk-deepmind-founders-and-others-promise-not-to-make-lethal-ai-weapons/#165c8a1b7269 The signatories have promised to “neither participate in nor support the development, manufacture, trade,… Continue reading →

A big step towards making devices like Alexa or Siri (or more likely Google Assistant, given that this research comes from DeepMind) better understand humans is the development of "theory of mind". By around 4 years old, human children can understand that their beliefs may diverge from those of others, and that understanding that divergence can help predict likely future behaviour of others – applying this to human interaction might make the experience more natural. A first step, DeepMind's algorithm is able to analyse the behaviour of AI systems which are otherwise too complex for people to understand and to… Continue reading →

Among many promising applications for AI in medicine, cardiology is one with the greatest potential. Current clinical practice calls for manual analysis of a wide range of complex diagnostic imagery, and this analysis is time consuming and error prone, even for the most experienced doctors. Advances in the technology are hampered by ethical concerns that augmenting human decisions with AI violates the relationship between doctor and patient. https://www.news-medical.net/health/Artificial-Intelligence-in-Cardiology.aspx The continuous development of the technological sector has enabled the industry to merge with medicine in order to create new integrated, reliable, and efficient methods of providing quality health… Continue reading →

Following the controversy around (and expiration of) Google's $15 million contract with the US Department of Defense (https://mashable.com/2018/06/02/google-defense-department-project-maven-contract-not-renewed/?europe=true#ebCfKFgiPPqN), the US government has now signed an $885 million contract with Booz Allen – and i'm willing to bet that there will be far less public debate around the ethics of the applications of technology under this contract than with Google. https://blogs.wsj.com/cio/2018/07/30/pentagon-signs-885-million-artificial-intelligence-contract-with-booz-allen/ The U.S. Department of Defense will for the first time be using large-scale AI systems that could automate mundane tasks and augment the work of military members. The contract also will go toward… Continue reading →

Yet another example of the value of simulated training, researchers at OpenAI trained a robotic hand using hundreds of years of  object manipulation inside a computer simulation. The resulting hand movements are significantly more dexterous than anything developed so far. https://www.technologyreview.com/s/611724/artificial-intelligence-driven-robot-hand-spends-a-hundred-years-teaching-itself-to-rotate/ A reinforcement-learning algorithm allows Dactyl to learn physical tasks by practicing them in a virtual-reality environment. Continue reading →