Category Archives: Machine Learning

In 1950, Alan Turing developed the Turing test to answer the question can machines think? Since then, machine learning has gone from being just a concept, to a process relied on by some of the worlds biggest companies. Here Sophie Hand, UK country manager at industrial parts supplier EU Automation, discusses the applications of the different types of machine learning that exist today.

Machine learning is a subset of artificial intelligence (AI) where computers independently learn to do something they were not explicitly programmed to do. They do this by learning from experience leveraging algorithms and discovering patterns and insights from data. This means machines dont need to be programmed to perform exact tasks on a repetitive basis.

Machine learning is rapidly being adopted across several industries according to Research and Markets, the market is predicted to grow to US$8.81 billion by 2022, at a compound annual growth rate of 44.1 per cent. One of the main reasons for its growing use is that businesses are collecting Big Data, from which they need to obtain valuable insights. Machine learning is an efficient way of making sense of this data, for example the data sensors collect on the condition of machines on the factory floor.

As the market develops and grows, new types of machine learning will emerge and allow new applications to be explored. However, many examples of current machine learning applications fall into two categories; supervised learning and unsupervised learning.

A popular type of machine learning is supervised learning, which is typically used in applications where historical data is used to develop training models predict future events, such as fraudulent credit card transactions. This is a form of machine learning which identifies inputs and outputs and trains algorithms using labelled examples. Supervised learning uses methods like classification, regression, prediction and gradient boosting for pattern recognition. It then uses these patterns to predict the values of the labels on the unlabelled data.

This form of machine learning is currently being used in drug discovery and development with applications including target validation, identification of biomarkers and the analysis of digital pathology data in clinical trials. Using machine learning in this way promotes data-driven decision making and can speed up the drug discovery and development process while improving success rates.

Unlike supervised learning, unsupervised learning works with datasets without historical data. Instead, it explores collected data to find a structure and identify patterns. Unsupervised machine learning is now being used in factories for predictive maintenance purposes. Machines can learn the data and algorithms responsible for causing faults in the system and use this information to identify problems before they arise.

Using machine learning in this way leads to a decrease in unplanned downtime as manufacturers are able to order replacement parts from an automation equipment supplier before a breakdown occurs, saving time and money. According to a survey by Deloitte, using machine learning technologies in the manufacturing sector reduces unplanned machine downtime between 15 and 30 per cent, reducing maintenance costs by 30 per cent.

Its no longer just humans that can think for themselves machines, such as Googles Duplex, are now able to pass the Turing test. Manufacturers can make use of machine learning to improve maintenance processes and enable them to make real-time, intelligent decisions based on data.

The rest is here:
What is the role of machine learning in industry? - Engineer Live

Fleet Owner returned to CES, the annual mega technology show in Las Vegas, in search of potential transportation technology that could help fleets of the future. Here are some news and notes from the more than a million square feet of exhibit space. You can read our coverage of other news out of CES here: (DOT on autonomous vehicles,Peterbilt,Kenworth and Dana,Bosch and ZF,BlackBerry, andmore).

Plus.ai announced at CES 2020 it will expand testing of its self-driving trucks to cover all permissible continental states in the U.S. by the end of 2020. This will include closed-course testing and public road testing, with a safety driver and operations specialist onboard to assume manual control if needed.

"We want to build a technology solution that is applicable across different weather, terrains, and driving scenarios, said Shawn Kerrigan, COO and co-founder ofPlus.ai. Testing our trucks readiness means we need to put them through stringent safety tests, on every highway in the country.

Plus.ai has conducted autonomous truck testing in 17 states: Arizona, California, Colorado, Illinois, Indiana, Kansas, Minnesota, Missouri, Nevada, New Mexico, Ohio, Pennsylvania, South Dakota, Texas, Utah, West Virginia and Wyoming.

"Thesmart mobility ecosystem weve established in Ohiois a premier testing ground for autonomous vehicles," said Patrick Smith, interim executive director ofDriveOhio. Ohio is excited to welcome leading autonomous trucking companies like Plus.ai to test at our state-of-the-art facilities and infrastructure.

Plus.ai expects that the new testing sites and states will be selected by the spring and implementation will take place through the rest of the year.

Ryder's outdoor booth at CES 2020 featured a Nikola Two truck.Josh Fisher/Fleet Owner

Ryder System was among the trucking and logistics companies exhibiting at CES this year. And helping the company catch the eye of attendees was the Nikola Two tractor on display at its outdoor booth that focused on the future of transportation logistics and equipment.

Ryder is showing current and potential leasing customers what is available now and around the corner in electric and automated trucks and how they can help increase supply chain efficiency.

Bridgestone made its first appearance at CES, and highlighted its mobility solutions that look toward an autonomous future focused on extended mobility, improved safety and increased efficiency.

The company showed off its future airless tires, smart tire technology and its Webfleet Solutions platform. That platform uses data and analytics to move millions of vehicles as efficiently as possible.

"Bridgestone has a nearly 90-year history of using technology and research to develop advanced products, services and solutions for a world in motion," said TJ Higgins, global chief strategic officer of Bridgestone. As we look to the future, we are combining our core tire expertise with a wide range of digital solutions to deliver connected products and services that promote safe, sustainable mobility and continue contributing to society's advancement."

The company's CES showcase demonstrated how airless tires from Bridgestone combine a tire's tread and wheel into one durable, high-strength structure. This design eliminates the need for tires to be filled and maintained with air.

The company also showed how its digital twin and connected tire technology can be used to generate specific, actionable predictions that can enhance the precision of vehicle safety systems.

The Bosch Virtual Visor uses LCD and AI technology to keep a driver's eyes in the shade.Bosch Global

Bosch unveiled what is called the most drastic improvement to the 100-year-old sun visor.

The Virtual Visor links an LCD panel with a driver or occupant-monitoring camera to track the suns casted shadow on the drivers face.

The system uses artificial intelligence to locate the driver within the image from the driver-facing camera. It also utilizes AI to determine the landmarks on the face including where the eyes, nose and mouth are located so it can identify shadows on the face.

The algorithm analyzes the drivers view, darkening only the section of the display through which light hits the drivers eyes. The rest of the display remains transparent, no longer obscuring a large section of the drivers field of vision.

We discovered early in the development that users adjust their traditional sun visors to always cast a shadow on their own eyes, said Jason Zink, technical expert for Bosch in North America and one of the co-creators of the Virtual Visor. This realization was profound in helping simplify the product concept and fuel the design of the technology.

This use of liquid crystal technology to block a specific light source decreases dangerous sun glare, driver discomfort and accident risk; it also increases driver visibility, comfort and safety.

The World Economic Forum and Deepen AI unveiled Safety Pool, a global incentive-based brokerage of shared driving scenarios and safety data for safe autonomous driving systems.

Aptiv was one of the first publicly announced members of the initiative.

"At Aptiv, we believe that our industry makes progress by sharing, especially when it comes to safety. We are proud to be part of the World Economic Forum's Safety Pool, and we are confident that with continued collaboration, we will deliver the safer and more accessible mobility solutions our communities deserve," said Karl Iagnemma, Aptivs president of autonomous mobility.

Safety Pool is gathering a vast and diverse set of driving scenarios and safety data from the major industry players developing ADAS systems and autonomous driving technology, it was announced at CES 2020. Data will be accessible by the members while an incentive scheme ensures the right value is taken and given by every Safety Pool participant, regardless of their size, level of funding, or years of operations.

According to Deepen, WEF and the first publicly announced Safety Pool pioneering members, sharing this data on such a large scale will generate tremendous positive externalities for the whole industry.

Each company developing ADAS systems and autonomous driving technology will have the chance to tap into a massive, common and shared database of driving scenarios on which to train and validate their machine learning models. In this way, the overall safety of operations will drastically increase, accelerating time to deployment.

See the original post:
BlackBerry combines AI and machine learning to create connected fleet security solution - Fleet Owner

It seems like AI is everywhere these days, from the voice recognition software in our personal assistants to the ads that pop up seemingly at just the right time. But believe it or not, the field is still in its infancy.

That means there's no better time to get in on the ground floor. The Essential AI & Machine Learning Certification Training Bundle is a one-course package that can give you a broad overview of AI's many uses in the modern marketplace and how to implement them.

The best place to dive into this four-course master class is with the Artificial Intelligence (AI) & Machine Learning (ML) Foundation Course. This walkthrough gives you all the terms and concepts that underpin the entire science of AI.

Later courses let you get your hands dirty with some coding, as in the data visualization class that focuses on the role of Python in the interpretive side of data analytics. There are also separate courses on computer vision (the programming that lets machines "see" their surroundings) and natural language processing (the science of getting computers to understand speech).

The entire package is now available for Boing Boing readers at 93% off the MSRP.

Former Vice President and current 2020 Democratic presidential hopeful Joe Biden says U.S. Section 230 should be immediately revoked for Facebook and other social media platforms, and that Mark Zuckerberg should be submitted to civil liability.

FBI needs to be able to hack into your iphone, Trumps sham AG William Barr says

Gee, thanks.

The latest iPhone cameras are undeniably impressive, but theyre still no match for a professional camera when it comes to taking clear, wide-angle shots. These six accessories will transform your iPhone into a pro-level camera in seconds, thanks to powerful and easy-to-attach lenses. 1. Lemuro 18MM iPhone Wide Lens MSRP: $100 | Sale Price: $80 []

Few things in life are more universally dreaded than going to the gym, which is unfortunate since a new year usually means making new resolutions to get in shape. Thankfully, this BodyBoss 2.0: Portable Home Gym has everything you need to burn fat and build muscle in the comfort of your own home. With just []

If one of your New Years resolutions is to travel more, you owe it to yourself to learn the language of the place youre visiting. If youre not sure where to start, give these resources a look. From mobile apps to online courses, these products can get you conversant in a new language before you []

Read the original:
Break into the field of AI and Machine Learning with the help of this training - Boing Boing

Raleys has brought artificial intelligence to pricing not to necessarily to go toe-to-toe with competitors, but to differentiate from them, President and CEO Keith Knopf said.

Speaking in a presentation at the National Retail Federation show in New York, Knopf described how the West Sacramento, Calif.-based food retailer is using machine learning algorithms from partner Eversight to help manage its price perception amid larger, and often cheaper, competitorswhile optimizing revenue by driving unit share growth and margin dollars. That benefit is going toward what he described as a differentiated positioning behind health and wellness.

This is not just about pricing for the sake of pricing. This is pricing within a business strategy to differentiateand afford the investment in price in a way that is both financially sustainable and also relevant to the customer, Knopf said.

Raleyshas been working with Eversight for about four years, and has since invested in the Palo Alto, Calif.-based provider of AI-led pricing and promotion management. Knopf described using insights and recommendations derived from Eversights data crunching to support its merchants, helping to strategically manage the Rubiks Cube of pricing and promoting 40,000 items, each with varying elasticity, in stores with differing customer bases, price zones and competitive characteristics.

Raleys, Knopf said, is high-priced relative to its competitors, a reflection of its sizeand its ambitions. Were a $3 billion to $4 billion retailer competing against companies much larger than us, with much greater purchasing power and so for us, [AI pricing] is about optimization within our brand framework. We aspire to be a differentiated operator with a differentiated customer experience and a differentiated product assortment, which is guided more toward health and wellness. We have strong position in fresh that is evolving through innovation. But we also understand that we are a high-priced, high-cost retailer.

David Moran, Eversights co-founder, was careful to put his companys influence in perspective. Algorithms don't replace merchants or set a strategy, he said, but can support them by bringing new computing power that exceeds the work a merchant could do alone and has allowed for experimentation with pricing strategies across categories.In an example he shared, a mix of price changessome going up, others downhelped to drive overall unit growth and profits in the olive oil category.

The merchants still own the art: They are still the connection between the brand positioning, the price value perception, and they also own the execution, Knopf said. This technology gets us down that road much faster and with greater confidence.

Knopf said he believes that pricing science, in combination with customer relationship management, will eventually trigger big changes in the nature of promotional spending by vendors, with a shift toward so-called below the line programs, such as everyday pricing and personalized pricing, and less above the line mass promotions, which he believes are ultimately ineffective at driving long-term growth.

Every time we promote above the line, and everybody sees what everybody else does, no more units are sold in totality in the marketplace, it's just a matter of whos going to sell this week at what price, Knopf said.I believe that its in in the manufacturers best interest, and the retailers best interest, to make pricing personalized and relevant, and the dollars that are available today will shift from promotions into a more personalized, one-on-one, curated relationship that a vendor, the retailer and the customer will share.

Excerpt from:
Raleys Drive To Be Different Gets an Assist From Machine Learning - Winsight Grocery Business

NASSAU, BAHAMAS Doctors Hospital has depriortized its medical tourism program and is now more keenly focused on incorporating artificial intelligence and machine learning in healthcare services.

Dr Charles Diggiss, Doctors Hospital Health System president, revealed the shift during a press conference to promote the 2020 Bahamas Business Outlook conference at Baha Mar next Thursday.

When you look at whats happening around us globally with the advances in technology its no surprise that the way companies leverage data becomes a game changer if they are able to leverage the data using artificial intelligence or machine learning, Diggiss said.

In healthcare, what makes it tremendously exciting for us is we are able to sensorize all of the devices in the healthcare space, get much more information, use that information to tell us a lot more about what we should be doing and considering in your diagnosis.

He continued: How can we get information real time that would influence the way we manage your conditions, how can we have on the backend the assimilation of this information so that the best outcome occurs in our patient care environment.

Diggiss noted while the BISX-listed healthcare provider is still involved in medical tourism, that no longer is a primary focus.

We still have a business line of medical tourism but one of the things we do know pretty quickly in Doctors Hospital is to deprioritize if its apparent that that is not a successful ay to go, he said.

We have looked more at taking our specialities up a notch and investing in the technology support of the specialities with the leadership of some significant Bahamian specialists abroad, inviting them to come back home.

He added: We have depriortized medical tourism even though we still have a fairly robust programme going on at our Blake Road facility featuring two lines, a stem cell line a fecal microbiotic line.

They are both doing quite well but we are not putting a lot of effort into that right now compared to the aforementioned.

Go here to read the rest:
Doctor's Hospital focused on incorporation of AI and machine learning - EyeWitness News

After a while, everything is overhyped and underwhelming. Even Artificial Intelligence has not been able to escape the inevitable reduction that follows such excessive hype. AI is everything and everywhere now and most of us wont even blink if we are toldAI is poweringsomeonestoothbrush. (It probably is).

The phrase is undoubtedly being misused but is the technology too? One thing is certain, whether we like it or not, whether we understand it or not, for good or bad, AI is playing a huge part in our everyday life today huger than we imagine. AI is being employed in health, wellness and warfare; it is scrutinizing you, helping you take better photos, making music, books and even love. (No, really. The first fully robotic sex doll is being created even as you are reading this.)

However, there is a sore lack of understanding of what AI really is, how it is shaping our future and why it is likely to alter our very psyche sooner or later. There is misinformation galore, of course. Either media coverage of AI is exaggerated (as if androids will take over the world tomorrow) or too specific and technical, creating further confusion and fuelling sci-fi-inspired imaginations of computers smarter than human beings.

So what is AI? No, we are not talking dictionary definitions here those you can Google yourself. Neither are we promising to explain everything that will need a book. We are onlyhoping to give you aglimpse into theextraordinary promise and peril of this single transformative technology as Prof Stuart Russell, one of the worlds pre-eminent AI experts, puts it.

Prof Russell has spent decades on AI research and is the author of Artificial Intelligence: A Modern Approach, which is used as a textbook on AI in over 1,400 universities around the world.

Machine learning first

Otherexperts believe our understanding of artificial intelligence should begin with comprehending machine learning, the so-called sub-field of AI butone that actually encompasses pretty much everything that is happening in AI at present.

In its very simplest definition, machine learning is enabling machines to learn on their own. The advantages of thisare easy to see. After a while, you need not tell it what to do it is your workhorse. All you need is to provide it data and it will keep coming up with smarter ways of digesting that data, spotting patterns, creating opportunities in short doing your work better than you perhaps ever could. This is the point where you need to scratch the surface. Scratch and you will stare into a dissolving ethical conundrum about what machines might end up learning. Because, remember they do not (cannot) explain their thinking process. Not yet, at least. Precisely why, the professor has a cautionary take.

The concept of intelligence is central to who we are. After more than 2,000 years of self-examination, we have arrived at a characterization of intelligence that can be boiled down to this: Humans are intelligent to the extent that our actions can be expected to achieve our objectives. Intelligence in machines has been defined in the same way: Machines are intelligent to the extent that their actions can be expected to achieve their objectives.

Whose objectives?

The problem,writes the professor, is in this very definition of machine intelligence. We say that machines are intelligent to the extent that their actions can be expected to achieve their objectives, but we have no reliable way to make sure that their objectives are the same as our objectives. He believes what we should have done all along is to tweak this definition to: Machines are beneficial to the extent that their actions can be expected to achieve our objectives.

The difficulty here is of course that our objectives are in us all eight billion of us and not in the machines. Machines will be uncertain about our objectives; after all we are uncertain about them ourselves but this is a good thing; this is a feature, not a bug. Uncertainty about objectives implies that machines will necessarily defer to humans they will ask permission, they will accept correction and they will allow themselves to be switched off.

Spilling out of the lab

This might mean a complete rethinking and rebuilding of the AI superstructure. Perhaps something that indeed is inevitable if we do not want this big event in human history to be the last, says the prof wryly. As Kai-Fu Lee, another AI researcher, said in an interview a while ago, we are at a moment where the technology is spilling out of the lab and into the world. Time to strap up then!

(With inputs from Human Compatible: AI and the Problem of Control by Stuart Russell, published by Penguin, UK. Extracted with permission.)

Visit link:
Being human in the age of Artificial Intelligence - Deccan Herald