According to ZDNet, LG CNS has deployed an AI-powered, facial recognition gate control service at its Seoul headquarters.
The gate control service was created in partnership “with Chinese AI firm SenseTime, uses a designated reader that can identify a face, authenticate an employee, and open the gate, all within 0.3 seconds, according to LG CNS.” Even more impressive, the technology is 99% accurate and can read faces two meters away, “even if the person wears a mask, glasses, make-up, or positions their heads at an angle.”
The new technology could simultaneously increase corporate security while reducing bottlenecks. By relying on facial scans, the system eliminates the risk of lost keycards, hacked authentication codes or stolen fingerprints. Thanks to the 0.3 second scan time and two meter range, employees can walk right in without slowing down or stopping.
ZDNet reports the facial recognition tech has been deployed at “26 gates so far at LG CNS’s headquarters, with the company hoping to eventually expand the new gate control service to up to 27,000 access points operated by LG CNS for 170 of its domestic and global clients.”
Given the benefits facial recognition offers, it’s likely only a matter of time before companies large and small start converting to similar solutions.
Artificial intelligence (AI) on the edge is a critical factor to widespread AI adoption and ARM is tackling the problem head-on with a pair of new chips, according to The Verge.
Edge AI is the ability to run AI locally, on-device, rather than offloading to a remote server. The obvious benefits are increased speed, since there’s no latency back and forth between the remote server, as well as increased privacy.
According to The Verge, ARM is working on “the Arm Cortex-M55 and the Ethos-U55, a neural processing unit meant to pair with the Cortex-M55 for more demanding use cases.” The Cortex-M55 provides up to 15 times better machine learning performance and up to 5 times better digital signal processing performance than previous Cortex-M processors.
Unlike Intel or AMD, ARM doesn’t manufacture its own processors. Instead, it designs them and then licenses those designs to other companies, such as Apple, who go on to manufacture and use them. With these new chips, however, ARM isn’t targeting phones and tablets. The goal is to use the chips to “develop new Internet of Things devices, bringing AI processing to more devices that otherwise wouldn’t have those capabilities.”
If the Cortex-M55 lives up to the hype, it should help usher in a whole new generation of AI-enabled devices and services.
Artificial Intelligence is on the rise, as well as the market for people and science composing the technology. To be clear, Data science is the use of math, data, AI, and The Scientific Method. Data science allows data scientists to solve complex problems. Data scientists do a lot and have the reach to change the world- and employers have taken notice. Jobs listings for “data scientists” grew 15,000% between 2011 and 2012; and today, anyone can be a data scientist – you just need a little specialized training.
In a nutshell, data scientists do three things: build artificial intelligence software, create new technology, and change the world. The extrapolations data scientists find provide actionable business intelligence to many different industries, which means that data scientists have the potential to have a greater impact on the economy of the future than many CEOs.
AI software is built easily, all it takes is a data scientist’s combination of creativity and reality. The new technology data scientists create include autonomous vehicles, space exploration, & personalized medication and education tools. This can be to revolutionize the world on a scale beyond social opinion. Data science technology often caters to energy optimization, wildlife migration monitoring, and radical efficiency.
Although artificial intelligence and data science are trends of today, the journey of data science is a 3-century-long story. It all goes back to the 1740s with Bayes’ Theorem, stating that any initial belief, combined with new data, will provide an improved belief. Bayes’ Theorem went on to become the basis for very probability calculations powering today’s AI. Data was completely revolutionized in 1954 when Leonard Jimmie Savage explained the scientific objectivity of data analysis. This went on to become the foundations of statistics, and results began proving more objective with more data.
Today, data science has fully infiltrated the common vernacular. In fact, the bulk of all data in existence today (90%) was created within the last 2 years – reported by IBM in 2013. By 2025, we will be moving at a pace creating 175 billion terabytes of data every day. Going forward, more data will continue to be generated every two years than in all the years prior for quite some time.
To prepare, as well as to understand the world’s surging data, advanced tools are needed. More directly, data scientists are more hireable than ever. Throughout 2020, there will be over 2.7 million data scientist job openings. Data scientists with skills in Python, R, PyTorch, Hadoop, and Spark hold higher chances of finding success. Specifically, data engineers, software engineers, and AI Hardware Specialists are in high demand. In common, all data scientists will need a background in mathematics and computer science – knowing Java, SQL, Scikit-learn, SaaS, AForge.NET, or machine learning techniques puts you ahead of the race.
Data science is the future, and it’s a very cool and in-demand career with great job security and stability, as well as room to grow. To read more on the job economy for data scientists, scroll down.
In an effort to get ahead of the corona virus, China is turning to big data and artificial intelligence to help identify those infected.
According to the International Business Times (IBT), “several Chinese tech firms have developed apps to help people check if they have taken the same flight or train as confirmed virus patients, scraping data from lists published by state media.” The data is also giving officials the ability to track down individuals who may have been exposed, screen them and forecast how the disease will spread.
Baidu developed a system that uses infrared and AI-powered facial recognition to screen people at the railway station for a possible fever. Anyone with a temperature 99 degrees Fahrenheit or above is flagged for further checks. IBT reports that the “system can check more than 200 people a minute, far faster than the thermal scanners used at airports.”
Companies are also developing ways to both prevent the spread of the disease, as well as help those already infected. Some cities are using robots to scold people who are not wearing masks in public, while other companies are working on using drones to deliver medical supplies to the sick.
As China continues to struggle with the deadly outbreak, technology may well be the key to turning the tide.
It’s often difficult to comprehend how to get ahead of the competition – let alone adapt – when your business’ industry is constantly changing. Saying this, utilizing Enterprise AI can boost your business’ performance, quality, and position within the industry. However, if considering AI implementation, you must be serious from the beginning. Fewer than 1 in 3 businesses who pilot AI programs actually proceed to launching the technology; however, this is due to many reasons. Planning for the long-term and simply jumping in despite your lack of clarity can push your enterprise ahead of the game. It just takes a little planning.
If you believe AI isn’t right for your business, it’s time to reconsider. The majority of the top sectors consider AI pivotal to their achievements- including 70% of financial and insurance companies, 65% of retailers and technologists, and 55% of educators and manufacturers. Saying this, AI has been found to be professionally universal, applicable across many sectors: manufacturing, transportation, and even the supply chain and logistics. There are many different ways to utilize AI, making it an important part of technological advancement in any field.
More specifically, AI can enhance a business leader’s decision-making capabilities, help reduce waste, improve product quality, cement a business into their ever-changing market, lower energy costs, and meet rising demands. For example, AI can increase the time it takes for business leaders to come to conclusions on complicated decisions, while also strengthening the decision they make. AI can also increase production results, decrease overhead costs, and eliminate deadhead trips, wasted energy, excess expedites and inventory, and more. With this, 84% of the world’s business leaders consider AI to give them an advantage against their competition, strengthening the power of their business.
Moreover, many successful executives and business leaders have commented on their experiences with Enterprise AI. Paul Daughtery, Chief Technology and Innovation Officer says, “The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.”
In similar advice, Lee Blackstone (Founder of Blackstone+Cullen) noted, “You need to understand what you really need to automate and how it’s going to benefit you. How is AI going to change your business so that you can respond faster than your competitors?” Hence the reason getting started is the most important step in implementation.
No matter the industry, there’s a way to incorporate AI into your five-year strategy. It can be used to decrease production costs, reduce waste in shipping, make predictions about changing markets, and more. It can help many industries reduce energy costs and make better predictions about consumer behavior. It can take data and extrapolate the next steps in actionable ways that businesses can act upon.
Data is more important than ever, and Enterprise AI can enhance the way your business’ data is processed. The steps to incorporating and expanding AI into your business are simple. Read more information on Enterprise AI below.
In further proof that Clearview AI can’t be trusted, BuzzFeed News is reporting the facial recognition firm is planning on selling its services to authoritarian regimes.
Clearview claims to have scraped over 3 billion photos from millions of websites, including the major social media platforms. The company then makes those photos available, in a searchable database, to hundreds of law enforcement agencies across the country.
According to BuzzFeed, “a document obtained via a public records request reveals that Clearview has been touting a ‘rapid international expansion’ to prospective clients using a map that highlights how it either has expanded, or plans to expand, to at least 22 more countries, some of which have committed human rights abuses.”
Three of the countries are the United Arab Emirates, which is known for cracking down on dissidents, as well as Qatar and Singapore, both of which have far more restrictive human rights laws than Western countries.
In an interview with BuzzFeed, Albert Fox Cahn, a fellow at New York University and the executive director of the Surveillance Technology Oversight Project, expressed concern about the implications of the software being used by oppressive regimes.
“It’s deeply alarming that they would sell this technology in countries with such a terrible human rights track record, enabling potentially authoritarian behavior by other nations,” he said.
Clearview CEO Hoan Ton-That has been defending his company amid growing scrutiny and concern over the legality and ethics of its behavior. The New Jersey Attorney General recently enacted a moratorium on police departments using the company’s service. Twitter, Facebook, Google and YouTube have sent cease-and-desist letters to Clearview. Now, as lawmakers increasingly turn their attention toward the company, it’s a safe bet this latest news will not help Clearview’s case.
The California DMV has granted Uber a permit to test its vehicles on California roads, according to The Mercury News.
Self-driving cars are increasingly seen as a way for Uber to deal with regulation that threatens how it does business. In Germany, the company was recently banned from transporting customers using rental vehicles after previously being blocked from matching riders with drivers using their own vehicles. In California, Uber is facing additional challenges as a result of Assembly Bill 5 (AB5) that changes the status of contractors to that of employees, requiring companies like Uber to offer additional benefits and thereby driving up costs.
Self-driving cars would solve these and other problems and potentially streamline long-term costs for Uber. The company has previously tested self-driving vehicles, with a car the company was testing notoriously striking and killing a pedestrian in Arizona.
The Mercury News is reporting that “the DMV said that it granted the permit to Uber’s Advanced Technologies Group after the company ‘fulfilled all the requirements to receive a permit to test autonomous vehicles in California with a safety driver behind the wheel.’ The DMV also said that Uber presented documentation that showed changes it made to its autonomous vehicle testing program and testing guidelines.”
There is no timetable for the cars to see widespread use, with Uber indicating it is in no hurry to deploy the vehicles.
“We just put out our latest research on Tesla,” says Ark Investment analyst Tasha Keeney. “We think over the next five years our expected value for the stock is $7,000 per share.” Tesla’s current share price is roughly $735 equating to a market cap of $132.4 billion. A $7,000 per share price would increase their current value tenfold. And that’s just Ark’s “expected” valuation. Ark’s bullish valuation is $15,000 a share, a $2.7 trillion market cap.
Keeney says it’s because Tesla is a leader in electric autonomous vehicles. “That’s the future of the auto market. What we’ve seen over the past year is that traditional autos have really struggled to produce EVs that are on par with Tesla’s cars and its data library. In terms of autonomous driving, it is really just running away from the competition.”
Tesla Has a Massive Advantage With Their Machine Learning Algorithms
In electric vehicles, Tesla is the leader and that’s because they’re writing down the battery cost decline curve. At Arc Invest we’ve actually done a lot of work using Wright’s Law to predict the future declines of batteries. Basically, for every cumulative doubling in production, you get a corresponding reduction in cost. We actually think that Tesla’s gross margins could go from say around 20 percent today, if you take out credits, to up to 40 in the best-case scenario. They also have not lost share in the electric vehicle market.
They’re sitting right around an 18 percent share. We think that they’re at least three years ahead of other automakers on a battery efficiency standpoint. That’s dollar per range that you get out of the car. Then on autonomous driving, they’re the only automaker that’s collecting data from their vehicles. This gives them a massive advantage in terms of training their machine learning algorithms to get the car to drive.
Our Case Is Really Driven By Autonomous Driving
We’ve devised a probability matrix where we’ve looked at the past year. We’ve seen what Tesla’s done in Shanghai and It’s amazing. They’ve built the factory in less than a year, and they’re right now shipping cars. Tesla’s shown that they can scale in a capital-efficient manner. We look at a few key variables. We look at capital efficiency, gross margins based on our Wright’s Law work, and autonomous driving. We set probabilities to each of those that help us arrive at that $7,000 mark.
Our bulk case is really driven by autonomous driving. This could be a huge opportunity for Tesla. It’s going to totally transform the business model if they pull it off. They’re going to get software like margins in a market that we think could be worth trillions of dollars globally.
Tesla’s In a Great Position To Be the Leader of the Future
Tesla’s been misinterpreted for a long time. One, on the autonomous driving front. You can’t value it like a traditional automaker because the future of the auto industry is changing. Electric vehicles and autonomous vehicles are going to make this a more consolidated market. A lot of automakers are going to go out of business and Tesla’s really in a great position to take advantage and be the leader of the future.
So again, if you look at autonomous driving that means software like multiples because we think they’ll get software like margins off of that business.
Report: Potential Tesla Valuation of $2.7 Trillion by 2024
According to the BBC, the English town of Blackpool is using artificial intelligence (AI) in an innovative way: to help fix potholes.
In most cases, road departments must either wait for reports of potholes, or proactively inspect roads. In either case, it may be days before road crews become aware of a pothole, increasing the likelihood it will get worse.
Blackpool, on the other hand, is using AI and satellite images to inspect roads in mere seconds. As a result, potholes are getting fixed much faster, before they have the opportunity to get worse. The end result is significant savings.
The Blackpool Council “said 5,145 potholes had been fixed in North Shore at a cost of just under £450,000, which would have cost £1.5m using traditional methods,” according to the BBC. The Council plans to use the savings to improve even more roads.
While fixing potholes may not be the first thing that comes to mind when someone thinks of AI, Blackpool’s example highlights the many unique ways the technology can help revolutionize a broad range of industries.
TechCrunch is reporting that New York City has made it abundantly clear autonomous delivery robots are not welcome.
FedEx, like Amazon and Postmates, has been experimenting with autonomous delivery robots, some of which were in NYC over the weekend to be previewed at the company’s Small Business Saturday event. After some of the bots—called Roxo—were spotted, Mayor Bill de Blasio and transportation officials wasted no time making their position known—again, despite the fact the bots were only there for a presentation and not actually delivering anything.
According to TechCrunch, “the mayor tweeted that FedEx didn’t receive permission to deploy the robots; he also criticized the company for using a bot to perform a task that a New Yorker could do. The New York Department of Transportation has sent FedEx a cease-and-desist order to stop operations the bots, which TechCrunch has viewed.
“The letter informs FedEx that its bots violate several vehicle and traffic laws, including that motor vehicles are prohibited on sidewalks. Vehicles that receive approval to operate on sidewalks must receive a special exemption and be registered.”
The bots use machine learning, in combination with an array of sensing technology and cameras to plot a safe route, while at the same time avoiding obstacles and obeying traffic or sidewalk rules.
While FedEx has been testing “the bots in Memphis, Tennessee as well as Plano and Frisco, Texas and Manchester, New Hampshire,” it’s a safe bet NYC won’t be seeing them anytime soon.
After eight years as CEO of IBM, Ginni Rometty is stepping down and Arvind Krishna has been elected to replace her, according to a company press release.
Rometty is the first woman to hold the top position at IBM and oversaw the company during a period of transformation and disruption within the tech industry. She led IBM as it dealt with the rise of cloud computing, artificial intelligence and more. During her tenure, the company bet big on the hybrid cloud market, as well as its acquisition of open-source software company Red Hat.
Arvind Krishna will pick up where Rometty left off. In fact, Krishna is responsible for some of IBM’s strategic moves under Rometty. Specifically, he was the architect of the Red Hat deal, and has been a staunch proponent of IBM’s hybrid cloud approach.
“Arvind is the right CEO for the next era at IBM,” said Rometty in the press release. “He is a brilliant technologist who has played a significant role in developing our key technologies such as artificial intelligence, cloud, quantum computing and blockchain. He is also a superb operational leader, able to win today while building the business of tomorrow. Arvind has grown IBM’s Cloud and Cognitive Software business and led the largest acquisition in the company’s history. Through his multiple experiences running businesses in IBM, Arvind has built an outstanding track record of bold transformations and proven business results, and is an authentic, values-driven leader. He is well-positioned to lead IBM and its clients into the cloud and cognitive era.”
Krishna struck an optimistic tone that IBM will continue to innovate and play a pivotal role in the tech industry.
“I am thrilled and humbled to be elected as the next Chief Executive Officer of IBM, and appreciate the confidence that Ginni and the Board have placed in me,” said Krishna. “IBM has such talented people and technology that we can bring together to help our clients solve their toughest problems. I am looking forward to working with IBMers, Red Hatters and clients around the world at this unique time of fast-paced change in the IT industry. We have great opportunities ahead to help our clients advance the transformation of their business while also remaining the global leader in the trusted stewardship of technology.”
Verizon has announced a partnership with Honeywell “to help utilities speed up and simplify the deployment of new communication-enabled, intelligent sensors and controls for the smart electric grid.”
Honeywell is one of the leading makers of building control systems, with their equipment powering some 10 million buildings. In recent years, the company has been pushing into Internet of Things (IoT) territory, working to deliver smart building and utilities technology. The partnership with Verizon is a significant step in that direction, providing the telecommunications component the company needs.
“Working with Honeywell on these next-generation solutions will enable the reliability and scalability of the communications needed to deliver smart metering, manage distributed energy resources, conserve water, and make the digital world work better for utilities and consumers,” said Jay Olearain, director, Enterprise Products and IoT at Verizon. “Our Connected Utilities solutions bring connectivity and computing capabilities to all kinds of IoT devices, helping companies like Honeywell grow their leadership positions in the utilities space and expand their business models into new market opportunities.”
Verizon says its edge computing will help Honeywell integrate artificial intelligence and machine learning into meters. This will open a whole new world of opportunities for utilities to better manage the grid and energy demands moving forward.
“The Honeywell portfolio of utility applications and analytics expands with the new capabilities of wireless IoT,” said Ann Perreault, director, Connected Utilities, Honeywell Smart Energy. “By taking advantage of an already built, cellular infrastructure, our utility customers can more quickly deploy new capabilities based on interoperable communications, allowing them to facilitate innovation. This means that it is easier and more cost effective for utilities to apply analytics to plan for energy demand and to integrate emerging new technologies including micro-renewable generation, electric vehicles, battery storage and semi-autonomous control into the next evolution of the grid.”
The partnership will initially involve Verizon’s LTE, but the companies are exploring the benefits 5G can bring to the table as it becomes more widely available.
IBM is using artificial intelligence (AI) to map the human brain and help track the progression of Huntington disease, according to a blog post.
Huntington’s disease is one of several neurodegenerative diseases that includes Alzheimer’s and Parkinson’s. The disease is an inherited disorder and has no cure. Early symptoms can be hard to spot and vary from one person to the next. According to IBM, “people with HD show symptoms that start as subtle cognitive and motor changes, but gradually develop into uncontrollable movements and dementia before eventually leading to death.”
To help researchers studying the disease, IBM teamed “with CHDI Foundation, a non-profit biomedical research organization devoted exclusively to collaboratively developing therapeutics that will substantially improve the lives of those affected by HD.” The goal of the collaboration is to use AI to spot patterns in brain scans that can give insights to the progression of the disease, even before symptoms are apparent.
The collaboration won’t immediately result in a cure, but it will offer patients better options for care as the disease progresses, as a result of being able to better monitor the progression. IBM attributes this to the fact that “from a technical point of view HD displays a number of features that distinguish it from other neurodegenerative disorders and not only guide treatment design, but also help us to better understand the disease. In particular, genetic tests make it possible to study its progression many years before the onset of symptoms. In fact, several large studies followed hundreds of people with and without the HD mutation over time (4a, 4b, 4c). This set-up is optimal for building AI models that can learn the earliest signs of the disease in the brain and can inform ongoing and future clinical changes.”
While there is still a long way to go in the fight against Huntington’s, IBM’s involvement is giant step in the right direction and will likely result in tangible qualify-of-life improvements for patients suffering with the disease.
IBM announced it has added artificial intelligence (AI) to its TRIRIGA facilities management solution.
TRIRIGA is an integration workplace management system, that helps customers manage their workspace and facilities. By utilizing existing real estate to its maximum potential, companies can reduce waste and save money on operating cost and real estate purchases.
According to the press release, “the new TRIRIGA Assistant, a smart, conversational AI tool which uses natural language processing to help users quickly and easily engage with the spaces around them. TRIRIGA Assistant can help remove the hassle of coordinating with colleagues to schedule and reserve conference rooms, submit service requests such as lighting and catering, or locate a colleague’s assigned workspace.”
IBM sees workplace management as a critical part of a company’s efforts, one that can improve workflows, boost productivity, cut costs and improve bottom lines.
“Employees and real estate are key elements to organizational growth and development, driving companies to create cost-effective and engaging workplaces that help attract and retain top talent,” said Kareem Yusuf, Ph.D., general manager, AI Applications, IBM. “The implementation of TRIRIGA with embedded AI provides corporations and facility managers with insights into how they can more effectively utilize space across their enterprise. This technology can help companies address the growing expectations of today’s modern workforce and achieve better business results.”
Facial recognition firm Clearview AI is facing a potential class-action lawsuit, while simultaneously being banned from being used by NJ police, according to separate reports by the New York Times (NYT) and CNET.
The NYT is reporting that Clearview has found itself in hot water with the New Jersey attorney general over its main promotional video it was running on its website. The video showed Attorney General and two state troopers at a press conference detailing an operation to apprehend 19 men accused of trying to lure children for sex, an operation that Clearview took at least partial responsibility for.
Mr. Grewal was not impressed with Clearview using his likeness in its promotional material, or in the potential legal and ethical issues the service poses.
“Until this week, I had not heard of Clearview AI,” Mr. Grewal said in an interview. “I was troubled. The reporting raised questions about data privacy, about cybersecurity, about law enforcement security, about the integrity of our investigations.”
Mr. Grewal was also concerned about the company sharing details of ongoing investigations.
“I was surprised they used my image and the office to promote the product online,” Mr. Grewal continued, while also acknowledging that Clearview had been used to identify one of the suspects. “I was troubled they were sharing information about ongoing criminal prosecutions.”
As a result of his concerns, Mr. Grewal has told state prosecutors in NJ’s 21 counties that police should not use the app.
At the same time, CNET is reporting an individual has filed a lawsuit in the US District Court for the Northern District of Illinois East Division and is seeking class-action status.
“Without obtaining any consent and without notice, Defendant Clearview used the internet to covertly gather information on millions of American citizens, collecting approximately three billion pictures of them, without any reason to suspect any of them of having done anything wrong, ever,” alleges the complaint. “Clearview used artificial intelligence algorithms to scan the facial geometry of each individual depicted in the images, a technique that violates multiple privacy laws.”
It was only a matter of time before Clearview faced the fallout from its actions. It appears that fallout is happening sooner rather than later.
In a recent Brookings Institution report, authors Mark Muro, Jacob Whiton and Robert Maxim make the case that better-paid, white-collar professionals are most at risk of losing their jobs to artificial intelligence.
As the report points out, past studies have had little actual data to go on and have, instead, relied on case studies and subject assessments to predict which jobs and industries were most vulnerable.
“What’s more, most research has concentrated on an undifferentiated array of ‘automation’ technologies including robotics, software, and AI all at once,” the report says. “The result has been a lot of discussion—but not a lot of clarity—about AI, with prognostications that range from the utopian to the apocalyptic.”
In contrast, a new method devised by Stanford University Ph.D. candidate Michael Webb compares job descriptions with AI-related patents, giving a higher degree of accuracy.
The new data shows that low-wage jobs will continue to be heavily impacted by automation and robotics. When it comes to true AI, however, “the present analysis suggests that better-educated, better-paid workers (along with manufacturing and production workers) will be the most affected by the new AI technologies, with some exceptions.”
Professions that have a high amount of predictive work, or pattern-oriented tasks are the kind of jobs AI is particularly well-suited to take over.
“At the high end of AI involvement, for example, are numerous well-paid occupations that had relatively low exposure in our earlier, all-encompassing automation analysis. They range from market research analysts and sales managers to programmers, management analysts, and engineers. Often analytic or supervisory, these roles appear heavily involved in pattern-oriented or predictive work, and may therefore be especially susceptible to the data- driven inroads of AI, even though they seemed relatively immune in earlier analyses.”
In addition, individuals “with graduate or professional degrees will be almost four times as exposed to AI as workers with just a high school degree.” The data also shows that high-tech metro areas will be more susceptible than most rural areas.
The original, in-depth report is 46 pages long and is a fascinating read, providing some all-new insights into the far-reaching impacts AI will have on all economic sectors.
Google has announced that its Data Search tool is out of beta and ready for prime time.
Data Search is a tool designed to provide an easy way to search the countless datasets that exist on the web. As Google explains in their post, “across the web, there are millions of datasets about nearly any subject that interests you. If you’re looking to buy a puppy, you could find datasets compiling complaints of puppy buyers or studies on puppy cognition. Or if you like skiing, you could find data on revenue of ski resorts or injury rates and participation numbers. Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets and find links to where the data is.”
Based on feedback the company has received from the beta period, Google has added a number of new features, including the ability to filter datasets, see maps of a region associated with a dataset, whether a dataset is available for free, better dataset descriptions and mobile support.
Organizations who have a dataset they want included in Data Search can ensure it’s added via an open standard.
“The number of datasets that you can find in Dataset Search continues to grow. If you have a dataset on your site and you describe it using schema.org, an open standard, others can find it in Dataset Search. If you know that a dataset exists, but you can’t find it in Dataset Search, ask the provider to add the schema.org descriptions and others will be able to learn about their dataset as well.”
Now that the tool is publicly available, Google is committed to continuing to improve it. The tool should be a valuable addition to a wide range of companies, researchers and consumers.
GitHub is using artificial intelligence (AI) and machine learning (ML) to recommend open software issues to address first, according to a blog post.
GitHub is a company that offers a version control hosting platform for software projects. The company was looking for a way to make it easier for new users and programmers to be able to contribute to projects. In May 2019, they rolled out their “good first issues” feature, which made recommendations for easy, low-hanging-fruit issues.
The first iteration of the feature relied on project maintainers to label issues. This “led to a list of about 300 label names used by popular open source repositories—all synonyms for either ‘good first issue’ or ‘documentation.’” Ultimately, this could lead to more work, leaving “maintainers with the burden of triaging and labeling issues. Instead of relying on maintainers to manually label their issues, we wanted to use machine learning to broaden the set of issues we could surface.”
As a result, GitHub has introduced a second iteration of the feature, with ML-based, as well as the original label-based, issue recommendations. The end result is that the system now surfaces “good first issues” in approximately 70% of repositories, as opposed to 40% with the first iteration.
GitHub plans on expanding this feature to add “ better signals to our repository recommendations to help users find and get involved with the best projects related to their interests. We also plan to add a mechanism for maintainers and triagers to approve or remove ML-based recommendations in their repositories. Finally, we plan on extending issue recommendations to offer personalized suggestions on next issues to tackle for anyone who has already made contributions to a project.”
The entire blog post is a fascinating read about how AI and ML can be used to transform even mundane tasks.
“AI is one of the most profound things we are working on as humanity,” says Google CEO Sundar Pichai. “It’s more profound than fire or electricity or any of the other bigger things we have worked on. It has tremendous positive sights to it but it has (potential) real negative consequences. When you think about technologies like facial recognition it can be used to benefit, it can be used to find missing people, but it can also be used for mass surveillance.”
Sundar Pichai, CEO of Google, discussed the massive potential for AI to change the world in a Bloomberg interview at the World Economic Forum’s annual meeting in Davos, Switzerland:
AI Is More Profound Than Fire or Electricity
AI is one of the most profound things we are working on as humanity. It’s more profound than fire or electricity or any of the other bigger things we have worked on. It has tremendous positive sights to it but it has (potential) real negative consequences. When you think about technologies like facial recognition it can be used to benefit, it can be used to find missing people, but it can also be used for mass surveillance.
As democratic countries with a shared set of values, we need to build on those values and make sure when we approach AI we are doing it in a way that serves society. That means making sure AI doesn’t have bias, that we build and test it for safety, and we make sure that there is human agency that is ultimately accountable to people.
We Need a Common Framework By Which We Approach AI
About 18 months ago we published a set of principles under which we would develop AI at Google. It’s been very encouraging to see the European Commissioners identifiy AI and sustainability as their top priorities. The US put out a set of principles last week and at the OECD or G20 they are talking about this. I think this is very very encouraging and I think we need a common framework by which we approach AI.
It’s an early start but I am very encouraged that they have a lot of commonalities and that’s because they are rooted in common human values. So I think it’s a great start but we need to get more specific and evolve it significantly. The European Commission is working on a white paper around AI and I think that’s an important first step. We all need to engage.
As a company, we are committed to engaging in the process but it’s going to need everyone from around the world. AI is no different from climate, you can’t get safety by just having one country or a set of countries working on it. You need a global framework to arrive at a safer world there.
AI Is More Profound Than Fire or Electricity, Says Google CEO Sundar Pichai
“The acquisition today of Fiix is a really exciting one,” says Rockwell Automation CEO Blake Moret. “It spans the gap that’s traditionally existed between manually entered keystroke data and real-time data that’s coming from the equipment itself. This helps take maintenance and automation really to a whole new level.”
Fiix Inc. is a privately-held, AI-enabled computerized maintenance management system (CMMS) company. Fiix, founded in 2008, is headquartered in Toronto, Ontario, Canada.
“We’re really taking manufacturing to a whole new level,” added Moret. “We’re taking the traditional operational technology and know-how that’s existed on the plant floor for so many years and we’re marrying that with IT technology and bringing those together. It’s really unlocking a whole new level of productivity across all the industries that we serve.”
Fiix’s cloud-native CMMS creates workflows for the scheduling, organizing, and tracking of equipment maintenance. It connects seamlessly to business systems and drives data-driven decisions. The company’s revenue grew 70% in 2019 with more than 85% recurring revenue.
“We believe that the future of industrial asset management is performance-based,” said Tessa Myers, vice president, product management, Software & Control, for Rockwell Automation. “With the addition of the Fiix platform and expertise, our customers will benefit from a 360-degree view of integrated data across automation, production, and maintenance, helping them to monitor and improve the performance of their assets and optimize how maintenance work is done.”
James Novak, Fiix CEO, said, “From the beginning, Fiix has been on a mission to connect maintenance and operations teams to the tools, resources, and technology they need to modernize and join the future of maintenance. Joining Rockwell Automation will allow us to help even more companies modernize maintenance and increase asset performance by connecting to industry-leading data, automation, and production systems.”
The company says that the addition of Fiix directly aligns with Rockwell Automation’s software strategy.
Rockwell Automation CEO Blake Moret also discussed their involvement with COVID treatments and the vaccine:
“We’re involved with virtually all of the manufacturers who are working on the treatments and the tests and the vaccines around the world for the COVID virus. We’re really helping them and helping the world to recover. So we’re involved in the formulation, the packaging, the tracing, and you obviously have to do this at unbelievable scale to be able to meet the need.”
Rockwell Automation Taking Manufacturing To Whole New Level
Artificial intelligence (AI) is quickly becoming the ‘next big thing’ in the technology industry, with ramifications that are only now being discovered. At least one Silicon Valley giant believes the development of AI needs to be further regulated.
In an op-ed for the Financial Times, Alphabet CEO Sundar Pichai lays out the case for stricter regulation over the development of AI. Pichai starts out citing examples of how Google’s AI developments are helping industries, including improving breast cancer screenings, weather forecasting and the company’s latest deal with Lufthansa to reduce the impact of flight delays.
Pichai then highlights the potential dangers of burgeoning technology, technology that can do a lot of good but also be used to cause tremendous harm. In the realm of AI, he cites deepfakes as an example. Deepfakes are a type of AI-assisted photo and video manipulation designed to make it appear as if someone has said or done something they haven’t by transposing their face or head onto another person’s body. Companies such as Facebook and Reddit have taken measures to minimize the damage deepfakes can do, but experts fear the worst is yet to come as the technology matures and advances.
As a result of the potential for AI to be used improperly or dangerously, Pichai outlines Google’s stand, including emphasizing the importance of companies taking responsibility for the technology they create, market and benefit from. Rather than simply opening Pandora’s Box and leaving others to sort out the mess, Pichai says companies have the responsibility to make sure the technology they create is used for good.
“Now there is no question in my mind that artificial intelligence needs to be regulated,” Pichai writes. “It is too important not to.”
The CEO goes on to highlight the European Union’s GDPR privacy laws as a “strong foundation” for future regulation. Given that Google has often been accused of not respecting user privacy, it’s encouraging to see Pichai cite one of the most comprehensive privacy regulations as a template for moving forward.
All in all, Pichai’s op-end is a fascinating insight into the thoughts of one of the individuals who has a tremendous influence over the future of AI and well worth a read in its entirety at the Financial Times.
