- Here’s one that was presented recently at a talk by one of Amazon’s top Machine Learning people:Artificial Intelligence: A system or service which can perform tasks that usually require human intelligenceThis is a fairly common way to define it.
- Here’s a similar formulation from Nathan Benaich in his post 6 areas of AI and machine learning to watch closely:The ultimate goal of AI […] is to build machines capable of performing tasks and cognitive functions that are otherwise only within the scope of human intelligence.One problem with this definition is that it means the state of being an instance of Artificial Intelligence is temporary.
- Just look at all the “What is the difference between Artificial Intelligence and Machine Learning?”
- Really, why should Machine Learning be defined in relation to AI?The slippery definition issue above can be looked at as follows: it is the term “Artificial Intelligence” looking for things to refer to.
- This is no more true now than it was 50 years ago but many smart people are utterly convinced of it.The term “Artificial Intelligence” has been around since the early days of computer science, when “thinking machines” were seen as the natural next step after programming basic logic.
The internet is awash with stories about something called Artificial Intelligence. Confusion around what it is is prompting many to proffer definitions of it, or corrections of wrong definitions…
Continue reading “Hashtag Artificial Intelligence – Katherine Bailey – Medium”
- Google has been working on a wide range of AI-based projects lately – earlier this week, it showed off one that can identify what you’re trying to draw and surface clean clipart that resembles your doodle.
- Its latest experiment is called Sketch-RNN, and it’s a neural network system that has learned to draw on its own by looking at roughly 5.5 million sketches from people who played Pictionary with Google’s AI-powered Quick, Draw!
- By triaging sketches in 75 different categories like cats, pigs and trucks, the AI can now draw basic representations of these things when presented with hand-drawn sketches.
- Sketch-RNN can also draw without the help of a starting sketch, and can even complete sketches that a human has started, but not finished.
- Sure, the sketches aren’t exactly photorealistic, but the idea here is to ‘train a machine to draw and generalize abstract concepts in a manner similar to humans’, and Google has achieved that.
Google’s latest experiment is a neural network system that has learned to draw by looking at roughly 5.5 million sketches from people who played pictionary.
Continue reading “Google used your pictionary sketches to teach its AI to draw”
- Facebook Messenger users across the US are now being prompted to send and request money transfers by an artificial intelligence-based feature that detects when a payment is being discussed in a conversation on the social media platform and responds with a suggestion designed to help the user complete that payment.
- “M offers suggestions by popping into an open conversation to suggest relevant content and capabilities to enrich the way people communicate and get things done,” the social media giant says.
- M may make a suggestion in a conversation relevant to one of the core actions, and then the M logo and suggestion will appear — it’s that simple.”
- Facebook began testing payments through its Messenger service in July 2016.
- The social media giant also updated its Messenger chatbot platform to enable bots to accept payments without having to send shoppers to external sites to complete the checkout process in September 2016.
Facebook Messenger users across the US are now being prompted to send and request money transfers by an artificial intelligence-based feature.
Continue reading “Facebook Messenger adds payment prompts using artificial intelligence • NFC World”
- They’ve developed an evolution strategy (no, it doesn’t relate much to biological evolution) that promises more powerful AI systems.
- Rather than use standard reinforcement training, they create a “black box” where they forget that the environment and neural networks are even involved.
- The technique eliminates a lot of the traditional cruft in training neural networks, making the code both easier to implement and roughly two to three times faster.
- In tests, a large supercomputer with 1,440 cores could train a humanoid to walk in 10 minutes versus 10 hours for a typical setup, and even a “lowly” 720-core system could do in 1 hour what a 32-core system would take a full day to accomplish.
- However, the practical implications are clear: neural network operators could spend more time actually using their systems instead of training them.
OpenAI researchers have developed an evolution strategy that promises more powerful AI systems. Rather than use standard reinforcement training, they create a
Continue reading “Researchers have developed an evolution strategy that promises more powerful AI systems”
- The workplace is going to look drastically different ten years from now.
- So what do we need to learn today about the jobs of tomorrow?
- The robots and computers of the future will be based on a degree of complexity that will be impossible to teach to the general population in a few short years of compulsory education.
- And some of the most important skills people will need to work with robots will not be the things they learn in computing class.
- However, it looks like human workers will not be replaced by automation, but rather workers will work alongside robots.
How Artificial Intelligence and the robotic revolution will change the workplace of tomorrow
Continue reading “How Artificial Intelligence and the robotic revolution will change the workplace of tomorrow”
- Eben Upton, founder of the Raspberry Pi Foundation, told the BBC: “It’s fantastic to see Google getting closer to the maker community.”
- Google has set up its very own survey and is asking makers what smart tools would be the “most helpful”.
- Google set to bring AI to Raspberry Pi computers
- Google is on its way to bringing artificial intelligence and machine learning tools to computer Raspberry Pi.
- “I’m particularly excited about the prospect of connecting Raspberry Pi to some of the machine learning work coming out of Google DeepMind in London, allowing us to build smart devices that interact in the real world.”
Take a look at this interesting tech…
Continue reading “Google set to bring AI to Raspberry Pi computers”
- Google’s AI Learns How To Code Machine Learning Software
- The Google Brain artificial intelligence research group has created a new machine learning system that can design machine-learning software.
- In their experiment, the researchers challenged their software to create machine learning systems.
- Short Bytes: A team of researchers at Google Brain AI research group has created an AI system that has designed its own machine learning software.
- The software that came up with these designs used the power of 800 GPUs.
A team of researchers at Google Brain AI research group has created an AI system that has designed its own machine learning software. The software that came up with these designs used the power of 800 GPUs
Continue reading “Google’s AI Learns How To Code Machine Learning Software — Bad News For Programmers?”