- The annual report for the company’s 2017 fiscal year, which ended on June 30, now includes six references to AI, up from zero in the previous annual report.
- And the company has plunked AI into its corporate vision statement, too.
- “Our strategic vision is to compete and grow by building best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with AI,” the company wrote in the annual report, which was released on Wednesday.
- For the sake of comparison, here’s last year’s version: “Our strategic vision is to compete and grow as a productivity and platform company for the mobile-first and cloud-first world.”
- For Microsoft watchers, that old tagline should sound very familiar — pretty much ever since he became CEO of Microsoft in 2014, Satya Nadella has repeatedly spoken of the “mobile-first and cloud-first world” that the company was trying to target.
Artificial intelligence has replaced mobile in the company’s overall mission in its 2017 annual report.
Continue reading “Microsoft just officially listed AI as one of its top priorities, replacing mobile”
- Deep learning neural networks — the likes of which power AlphaGo as well as the current generation of image recognition and language translation systems — are the best machine learning systems we’ve developed to date.
- While neurons use their various connections with each other to recognize patterns, “We are explicitly forcing the network to discover the relationships that exist” between pairs of objects in a given scenario, Timothy Lillicrap, a computer scientist at DeepMind told Science Magazine.When subsequently tasked in June with answering complex questions…
- In a pair of research papers presented at the 2017 International Joint Conference on Artificial Intelligence held in Melbourne, Australia last week, IBM submitted two studies: one looking into how to grant AI an “attention span”, the other examining how to apply the biological process of neurogenesis — that is,…
- It’s the same way that your doctor doesn’t tap your knees with that weird little hammer thing when you come in complaining of chest pain and shortness of breath.While the attention system is handy for ensuring that the network stays on task, IBM’s work into neural plasticity (how well memories…
- Basically the attention model will cover the short term, active, thought process while the memory portion will enable the network to streamline its function depending on the current situation.But don’t expect to see AIs rivalling the depth of human consciousness anytime soon, Rish warns.
Since the days of Da Vinci’s “Ornithoper”, mankind’s greatest minds have sought inspiration from the natural world for their technological creations. It’s no di…
Continue reading “IBM is teaching AI to behave more like the human brain”
- The company has spent a lot of time honing its facial recognition technology for the purpose of building a system that can recognize people in consumer photos, and it’s now bringing those same models to commercial customers.
- That provides a benefit to enterprise customers, because it means that Ever can continue optimizing its facial recognition model on its consumer data set without having to tap the data of their enterprise clients.
- Customers who license Ever’s APIs will be entitled to ongoing updates as the company continues to revise its models in the future.
- Ever chose to make its APIs available under a self-hosted license that provides ongoing service, support, and upgrades rather than through a cloud service because its customers wanted the flexibility for unlimited use and the ability to run Ever AI in their own data centers.
- Ever AI has the potential to power products like improved multi-factor authentication, since its facial verification technology can let companies ensure that the person who’s looking at a camera matches an image they have on file for the same identity.
Ever, maker of a consumer app for storing and organizing digital photos, is getting into the enterprise market. Today, the company announced Ever AI, a set of APIs that are supposed to provide a wide variety of visual intelligence capabilities to companies that need them.
Continue reading “Ever takes on Microsoft, Amazon, IBM, and others with AI facial recognition service”
- In Brief A music album called I AM AI, the featured single of which is set to release on August 21st, is the first album that’s entirely composed and produced by an artificial intelligence.
- The AI was developed by a team of professional musicians and technology experts, and it’s the the very first AI to compose and produced an entire music album.
- Check out the song “Break Free” in the video below:
As film composer Drew Silverstein, one of Amper’s founders, explained to TechCrunch, Amper isn’t meant to act totally on its own, but was designed specifically to work in collaboration with human musicians: “One of our core beliefs as a company is that the future of music is going to be created in the collaboration between humans and AI.
- That said, the team notes that, contrary to the other songs that have been released by AI composers, the chord structures and instrumentation of “Break Free” are entirely the work of Amper’s AI.
- Yet, while IAMAI may be the first album that’s entirely composed and produced by an AI, it’s not the first time an AI has displayed creativity in music or in other arts.
A music album called IAMAI, which is set to release on August 21st, is the first that’s entirely composed by an artificial intelligence.
Continue reading “The World’s First Album Composed and Produced by an AI Has Been Unveiled”
- In the latest installment of Singularity University’s web series, Future of Everything With Jason Silva, Silva takes a look at artificial intelligence.
- Surely to transform the world and the human race in ways that we can barely wrap our heads around,” Silva says.
- Forms of creativity will be unleashed that we can not even imagine, and we’re going to transcend what it means to be human.
In this episode of “Future of Everything With Jason Silva,” Silva takes a look at the transformational potential of artificial intelligence.
Continue reading “Artificial Intelligence”
- If you tell a computer system that all white people like the color orange and then tell it to find meaningful patterns to support that, it will.
- If you tell it that all black people own solid green t-shirts, it doesn’t dispute you, it’ll go prove you right with whatever patterns it can develop from the data it has.
- Again, chances are you won’t run the risk of creating a bigot-bot unless your robot does something like pass judgement on people, draw conclusions based on race, or tries to resurrect phrenology.
- That pattern can be interpreted in many ways, but in truth it only means one specific factual thing: there are less women on that website looking for truck driver jobs than men.
- Theoretically the amount of patterns an AI could see is endless, the computer will literally continue looking for patterns until it has a command to stop, reaches a predetermined stopping point, or runs out of power.
AI systems are being exploited to “prove” the ideas of bigots. Forcing computers to provide patterns to support unscientific results is a very real problem.
Continue reading “Robots are really good at learning things like racism and bigotry”
- I have not seen any significant use of AI in my own clinical practice during my time in Boston, but exciting developments in the last two years hold much promise.
- One of the potential benefits when integrating AI into medical practice is improvement of clinical decision making and diagnosis.
- The concept of using AI to provide clinical decision support systems for physicians has been studied in some medical specialties with varying degrees of effectiveness.
- Comparisons between the paradigms of machine learning based, knowledge based, and hybrid methods have not yielded a clear model on how AI best uses clinical data to arrive at a diagnosis.
- There is promise that Deep Learning methodology will allow for AI to train much like a medical resident does through a large data set of disease presentations.
A discussion on Dr. Michael Forsting’s article “Machine Learning Will Change Medicine” in the Journal of Nuclear Medicine.
Continue reading “Medicine in the Age of AI”
IBM and MIT today announced that IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT. The lab will carry out fundamental artificial intelligence (AI) research and seek to propel scientific breakthroughs that unlock the potential of AI.
Continue reading “IBM and MIT to pursue joint research in artificial intelligence, establish new MIT–IBM Watson AI Lab”
- While the merits of providing everyone with a minimum income have been debated for many years, the practicality of the government providing it to the people has been non-existent at least until recently.
- This is because the many services that government provides already, including welfare, healthcare, and the like are taking up so much in terms of money that simply providing every person with a minimum income seems like a simpler solution.
- What was once limited to science fiction, Artificial Intelligence (AI) has now become a part of the internet in helping businesses grow.
- For those in the low-income bracket, the future looks bright thanks to the many avenues available to help people make money through Microsoft, Google, Tesla, and other companies dedicated to providing economic access to the power.
- Big online companies such as Google and Microsoft for example can use their considerable pull to provide the following;
While the idea of a secure, minimum income has been around for several decades, it may come true thanks to the internet and the ability of large online companies to provide opportunities for millions of people who otherwise would be limited in how they could earn a living.
How Can We Guarantee a Secure Minimum Income for Everyone? How can it be achieved without damaging the fabric of society?Explore the answers in my article.
Continue reading “The Role of Artificial Intelligence in Growing Business”
- The process involved using a deep-learning framework called Caffe, and feeding it data-sets with images representative of different tattoo styles.
- Once the initial training session was complete, the AI could identify the style of a tattoo with pretty impressive accuracy.
- While the AI isn’t implemented into the app yet (they’re still feeding it data) they intend to finish training the AI then go forward from there.
- AI will help us to classify the remaining 250k pictures… Classification is really important for us because, based on it, we can show users personalized feeds depending on what styles they like, what artists they follow, what those artists are specialized in, etc.
- Without AI to sort images, a person has to view each one, decide what style it represents, tag the image, and then create hashtags so that other users can find it.
A pair of developers at Tattoodo developed a neural-network capable of processing pictures of tattoos and determining the style of the ink in the images.
Continue reading “These programmers taught an AI how to understand tattoos”