Here is the list of developments in machine learning & artificial intelligence happened during year 2015:
Torch, an open-source library that’s been around since 2002, contains a framework for building and training neural networks. Facebook is making several modules available via Torch, including one with a convolutional neural network layer featuring highly customized kernels and much more.
GraphLab is an open source project designed to help machines analyze graphs i.e. the online relationships between people and the stuff they use on the net. GraphLab, now Dato, launched their first commercial product. It received an additional $18.5 million in funding in January.
AI is the hot place at the moment. More than 170 start-ups have jumped on the AI bandwagon. Start-ups flocking to the field face some daunting competition. The biggest advances in AI are being made inside big tech groups such as Google, IBM and Facebook, which have invested heavily in the field.
This computer program is inspired by human brain and learnt to play 49 classic Atari games. Researchers from Google DeepMind achieved this successful feat. In 2014, Google purchased DeepMind Technologies for a reported £400m.
Azure Machine Learning is built on the machine learning capabilities already available in several Microsoft products including Xbox and Bing. It supports both R, Python, Hadoop, Spark and much more. The real strength of this platform is the ability to create APIs and begin processing data very quickly
Artificial Intelligence helped Ford to solve the problem of work out scheduling for the growing number of people in a three year program for new hires fresh out of college. This app was made using about 10,000 lines of code, spending about 20 hours programming and the Hungarian algorithm.
After many years of research, deep learning with neural networks is applied in virtual drug screening which attempts to replace or augment the high-throughput screening process with the use of computational methods. They used total of 37.8M data points across more than 200 distinct biological processes.
PayPal uses a champions-and-challengers approach to deciding which fraud-detection models to rely on most heavily, and deep learning is very close to becoming the champion. Once the models detect possible fraud, human “detectives” can get to work assessing what’s real, what’s not and what to do next.
Microsoft has built a ‘chit chat’ system into Cortana that lets her sing songs and do imitations. Machine Learning makes Cortana smart enough to crack jokes and predict sports matches, as well as tell you when to leave early for your meeting because the traffic is bad
Google made a deal with the healthcare company Johnson & Johnson to develop surgical robots that use artificial intelligence. The robots will aid surgeons in minimally invasive operations, giving operators greater control and accuracy than is possible by hand and minimizing damage to the patient.
Facebook developed a simple test that can help determine the intelligence level of an artificial intelligence software. This test involves 20 tasks, which get progressively harder. Any potential artificial intelligence (AI) must pass all of them if it is ever to develop true intelligence
This service got launched to developers of all skill levels to use machine learning technology. Once your models are ready, Amazon Machine Learning makes it easy to obtain predictions for your application using simple APIs.
PayPal uses three types of machine learning algorithms for risk management: linear, neural network, and deep learning. Experience has shown PayPal that in many cases, the most effective approach is to use all three at once.
Researchers at Yahoo Labs in Barcelona and California studied patterns of behavior in a database of 16 billion e-mails exchanged between two million people over several months
Google unveiled a new feature at I/O 2015 keynote which lets Android’s personal assistant examine whatever is happening on the screen and automatically take relevant actions.
Intel didn’t stay behind. Intel has designed its E7 chips to a fast-changing server market, where companies like Google, Facebook and Amazon have redefined data center designs. The companies claim the new chips are six times faster on leading enterprise applications
Airbnb has followed the belief that has enabled humans to partner with a machine in a symbiotic way exceeds the capabilities of humans or machines alone. This package has a thrift based feature representation designed from the ground to be human friendly.
SethBling made a bot MarI/O that automatically learns how to play Super Mario World. It used neural networks that evolve with a genetic algorithm.
Amazon launched a new machine learning system that understands which reviews are likely to be the most helpful, and floats them to the top. The artificial intelligence typically prefers reviews that are recent, receive a lot of up-votes or come from verified buyers.
Twitter said that the company will use Whetlab’s technology as an internal service to accelerate Twitter’s current machine learning efforts with an emphasis on deep learning and artificial intelligence.
Microsoft has showed interest in hiring people who can teach computers how to perform machine learning, which can make software smarter over time. An official said, ‘Machine learning has proved so useful that it’s created a supply and demand problem: There just aren’t enough people with machine learning expertise to do all the projects businesses and organizations want’
Using artificial intelligence, google translate app lets users translate text instantly. This handy feature has been available for some time, but it had only been compatible with seven languages. Now, thanks to machine learning, Google has upgraded the app to instantly translate 27 languages.
Hitachi has developed an “artificial intelligence” system that draws on a massive range of data sources, such as millions of news articles, and can provide a reasoned response to hot-button topics. The system currently has access to 9.7 million news articles and reports, indexed by what it describes as a web of 250 million correlations.
Paypal employs state of art machine learning and statistical models to flag fraudulent behavior upfront. More sophisticated algorithms are used to filter transactions. It also uses deep learning methods which helps to learn complex highly varying functions not present in the training examples.
This service is made available using AWS Dublin region. It is expected that availability of Amazon Machine Learning in this region will help to address limitations, organisations may have related to the location of their data, as all analytics and predictions will be done on data that resides in Europe and will not leave the region
Hype Cycle shows the emergence of technologies which supports digital humanism. It feature technologies which Gartner believes to have potential for significant impact. Machine Learning made its first appearance in 2015 Hype Cycle Report of Emerging Technologies. It holds the position at peak of inflated expectations on the curve.
Apple has boosted its efforts to recruit employees focused on artificial intelligence and machine learning. Apple is looking to challenge Google’s lead in features such as Google Now that learn to anticipate smartphone users’ needs, something Apple is starting to address in iOS 9 with its new”Proactive” feature.
LinkedIn’s FeatureFu project is a new open source toolkit designed to enable creative and agile feature engineering for most machine learning tasks such as statistical modeling (classification, clustering, and regression) and rule-based decision engines.
Twitter is attempting to supplement some of their machine learning engineers with actual machines. The theory is that, instead of an engineer spending weeks or months getting a spam detection system or a trending topics algorithm working as best as she possibly can, an algorithm could do most of that heavy lifting instead.
Perceptio, is a startup focused on bringing advanced image-classifying artificial intelligence to smartphones by reducing data overhead typically required of conventional methods. It is specialized in deep learningan arm of machine learning that relies on pattern-based processing to analyze and categorize input.
Hitachi developed a technology which uses a variety of data sources likely to have an impact on crime, including weather conditions, proximity to schools and subway stations, 911 (emergency) calls, gunshot sensors, population movements, and, of course, previous crime statistics.
Tesla’s new autopilot technology is constantly learning and improving thanks to machine learning algorithms, the car’s wireless connection, and detailed mapping and sensor data that Tesla collects. Tesla’s cars in general have long been using data, and over-the-air software updates, to improve the way they operate.
Fractal analytics has acquired Imagna Analytics, an artificial intelligence (AI) startup founded by Prashant Warier. This is Fractal’s second acquisition this year and will further strengthen Fractal’s IP in the area of Customer Genomics.
RankBrain is Google’s name for a machine-learning artificial intelligence system that’s used to help process its search results. It is a part of Google’s overall search “algorithm,” a computer program that’s used to sort through the billions of pages it knows about and find the ones deemed most relevant for particular queries.
Toyota announced a five-year, $1 billion research and development effort towards artificial intelligence. The new effort by Toyota is also the latest indication of a changing of the guard in Silicon Valley’s basic technology research. Toyota plans to hire 200 scientists for its artificial intelligence research center.
H2O is an open source platform for data scientists and developers who need a fast machine learning engine for their applications. Recently, the company has raised a $20 million Series B funding round led by Paxion Capital Partners (the new firm of GoPro board member Michael Marks) and existing investors Nexus Venture Partners and Transamerica.
Accenture has set up an artificial intelligence lab in Dublin, Ireland, joining existing labs in San Jose, Calif.; Arlington, Va.; Sophia Antipolis, France; Beijing, China; and Bangalore, India. The labs will collaborate with other Accenture teams to create more intelligent tools and much more.
Facebook is testing an artificial intelligence (AI) feature that will allow it to answer questions about a photo, a feature aimed at helping blind people “see” images uploaded to the social network. The U.S. giant has been pushing hard to develop its AI capabilities – alongside Apple and Google.