Large Language Model
The era of Artificial Intelligence: Issues and Concerns - indoona blog
The evolution of the AI programs is reaching many fields: for example, to allow the AI to communicate in an ever more human way, Google's DeepMind developers have started to make it read hundreds of romance novels to help it improve its dialectical skills and develop a minimum of personality. The choice fell on the romantic novels because they have very linear plots and simple narrative schemes but also they are very similar to each other, an element that AI can learn to manage and rework to interact with a human being. The next step is to draft long and elaborate sentences, or even writing entire novels. Not surprisingly, a recent book written by a computer has passed a literary prize screening. The Japanese literary prize Hoshi Shinichi is also open to works produced by artificial intelligences and the jury โ without knowing its origin โ admitted the book "The day a computer writes a novel", written by the program of a professor of the Hakodate Future University.
In a historic moment for AI, computers gain ability to generalize learning between activities ExtremeTech
Given the tensions surrounding AI at the moment, it's not surprising DeepMind is couching this breakthrough in the most mundane terms. The proffered example given in their Nature paper was DNC's ability to successfully navigate a London subway map from previous experience, finding the shortest path between specified points and inferring the missing links in randomly generated graphs. Finding an optimal route between locations is something we are already familiar with computers doing, so it's calculated to underwhelm.
AI can learn from data without ever having access to it
In recent months, security researchers have shown that machine learning algorithms can be reverse-engineered and made to expose user data, like personal photos or health data. So how can we protect that information? New research from OpenAI and Google shows a way to build AI that never sees personal data, but is able to function as if it had. Ian Goodfellow, a researcher at OpenAI, compares the system to medical school. "The doctors who teach in medical school have learned everything they know from decades of experience working with specific individual people, and as a side effect they know a lot of private medical histories," Goodfellow says.
DeepMind's differentiable neural computer helps you navigate the subway with its memory
In his best-selling 2011 book Thinking, Fast and Slow, Nobel Prize-winning economist Daniel Kahneman hypothesized that thinking could be broken down into two distinct processes -- aptly named fast and slow thought. The former is all about your gut, the initial automatic responses you have to things, while the later is calculated, reflective and time-consuming. A new algorithm from DeepMind is beginning to show us that so-called "slow" thinking may soon be within the reach of machine learning. In a new paper published in Nature, the Google subsidiary DeepMind explained a new approach to machine learning that uses something called a differentiable neural computer. Neural networks operate using what essentially amounts to a very sophisticated trial and error process, eventually arriving at an answer.
SpaceX founder fears 'evil dictators' will use artificial intelligence to attack the West
The Billionaire, who also runs a not-for-profit artificial intelligence research company, warned that the futuristic technology could be deadly if it falls into the wrong hands. He has previously said that the research company, OpenAI, wants to "contract large corporations who may gain too much power by owning super-intelligence systems devoted to profits, as well as governments which may use AI to gain power and even oppress their citizens" but has extended that warning further. Speaking to Sam Altman, co-chairman of OpenAI, he claimed that countries would attempt to steal control away from its owner. However, Mr Musk reassured the public that AI technology would not develop a mind of its own and attack like scenes fictionalised in science fiction hit Terminator.
Can DeepMind win 'Jeopardy' and Watson win 'Go'?
We are indeed living in interesting times, where we celebrate human-built machines defeating the best human minds at variety of activities. IBM Deep Blue's win against Chess champion Gary kasparov in 1997, IBM watson acing Jeopardy in 2011 and now Google DeepMind reportedly wining'Go' with high precision, being cited as a major breakthrough in AI, which even Facebook claims their team came close to acing the game as well. DeepMind goes against the'Go' champion, to be streamed live for the world to witness. While these feats are undoubtedly remarkable, and as understandable its creating quite a buzz in the AI community; as it provides the glimpse to the future seen only in sci-fi. As exciting as it may sound, it leaves a few questions before us.
Channel 4 hires Artificial Intelligence experts to build real robot that looks human
Along with taking part in the social experiment, Gemma will front the factual programme and delve into the advances that have been made into artificial intelligence. She will look at technology - such as driverless cars - and speak to British A.I. researcher Demis Hassabis and his DeepMind project, which is working toward creating machines that can learn even more by themsleves than ever before. "This film pushes the boundaries of what is possible using the technology that is increasingly influential in our lives," said Tom Porter, Channel 4's acting Commissioning Editor, Science.
Google's #DeepMind #artificialintelligence now can self-learn. It can teachโฆ
It can teach itself, The Next Web reported (17 Oct 2016): "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." The AI also knows how to optimise its memory to accelerate future searching-learning. The Next Web added: "Instead of having to learn every possible outcome to find a solution, DeepMind can derive an answer from prior experience, unearthing the answer from its internal memory rather than from outside conditioning and programming." In other AI news the British Socialist newspaper the Morning Star commented on the #Singularity and AI, regarding concern about powerful multinationals shaping AI (17 Oct 2016): "Technologies shaping our world and determining the sustainability of human civilisation are commissioned by wealthy corporations. So uploaded human intelligence, machine learning and systems designed without human agency -- and perhaps without human values -- are ideas we all need to understand and influence."
Google's DeepMind Revolutionizes Artificial Intelligence
The Google logo is displayed on a sign outside of the Google headquarters in Mountain View, California. Google's artificial intelligence (AI) platform DeepMind revolutionizes the field, being now capable of learning based on information already possessed. DeepMind is able of learning, or better said of teaching itself, based on data it already possesses. According to The Next Web, this is a significant step forward for artificial intelligence, a real breakthrough that revolutionizes the field. DeepMind technology is based on Alphabet's hybrid system called Differential Neural Computer (DNC).