Daily Archives: February 15, 2020

Even though the full optimization of AI and the IoT is relatively far away, the two technologies are now being combined across industries in scenarios where problem-solving and information can improve outcomes for all stakeholders.

Last such great convergence occurred in the late 1990s as mobile phones and the internet collided to change the course of human history. The convergence of AI and the IoT will bring in a similar revolution on an even grander scale.

AIoT Helps Companies Garner the Real Value of IoT Data

The ability to capture data through IoT is a large scale evolution that has exploded on the scene over the past five years. These new advancements have been accompanied by new concerns and threats associated with privacy and security. Large volumes of confidential company information and user data are tempting targets for dark web hackers as well as the global government entities. The high level of risk has also brought in newer and more responsibilities that accompany the increased capability.

Sensors are now applied to almost everything. This indicates that infinitely more data can be collected from every transaction or process in real-time. IoT devices are the front line of the data collection process in manufacturing environments and also in the customer service departments. Any device with a chipset can potentially be connected to a network and begin streaming data 24/7.

Complex algorithms allow performing predictive analytics from all conceivable angles. Machine learning (ML), a subset of AI, continues to upgrade workflows and simplify problem-solving. Companies now capture all the meaningful data surrounding their processes and problems to develop specific solutions for real challenges within the organization, improving efficiency, reliability, and sustainability.

While IoT and AI are impressive superpowers in their own capacity, thanks to the concept of convergence, their power doubles as IoT enhances the value of AI allowing real-time connectivity, data exchange, and signaling. AI enriches the capabilities of the IoT by applying ML to improve decision making.

Artificial Intelligence Trends for the Modern Enterprise

Industries are now referring to this convergence as AIoT. Presently, many AIoT applications are relatively massive, as companies build the expertise and required systems to deploy for supporting these powerful technologies across their organizations. The future will witness this convergence allowing more optimization and networking, creating even more value.

Experts have predicted a full digital integration between computers and humans by the year 2030. Between this and ongoing advances in robotics and automation, up to 40% of the current workforce could be replaced by technology in the next 10-15 years, by 2023. The predictions continue as:

Hardware manufacturers and solutions providers are already in full swing to leverage this tech convergence and position themselves in a position of favor in the evolving industrial landscape. Innovative companies like Amazon are offering training and re-education opportunities for employees in soon-to-be-obsolete job functions with such technology convergence hitting the market.

IoT Technologies Drive Digital Transformation Strategies of Enterprises

Convergence is a concept everyone should become familiar with, as every technology, discoveries, and advances will witness convergence in the future to innovate and disrupt the way the industries function.

Continued here:

AIoT Convergence of Artificial Intelligence with the Internet of Things - EnterpriseTalk

The growing use of artificial intelligence (AI) by police forces requires new vigilance on the part of courts and the public about finding the right balance between civil liberties and public safety, warns a professor at the University of California-Davis School of Law.

Law enforcement has been using computers for decades to handle large amounts of investigative information, but new technology such as facial recognition, Shot Spotter, financial anomaly detectio, and automated license plate camera readers, has allowed police to increase the scale and speed of processing information, writes Elizabeth E. Joh, a professor of criminal law and procedure, constitutional law, and policing at the U.C. Davis School of Law

Thatwarrants new scrutiny especially since many communities are unaware of the extent of advanced technology used by their law enforcement agencies, Joh wrote in an essay for Viewpoints, a newsletter published by the Association for Computing Machinery.

For example, the Chicago Police Department uses an algorithm that identifies which city residents may be at especially high risk as perpetrators or victims of gun violence.

Police in Fresno, Ca., piloted an alert system that tells an officer whether the driver the police officer just pulled over to the side of the road poses a threat.

Dozens of other police departments use a program called PredPol, a machine learning algorithm that maps granular 500 x 500-foot sections of the city where crime is more likely to occur, Joh reports.

One danger of the growing reliance on technology is that if the tools malfunction or are used incorrectly, serious consequences can result, according to Joh.

Artificial Intelligence removes human checks where police would traditionally enter a situation using their senses and basic skills to interpret what they are seeing.

Joh gives the example of a bystander reporting abuse.

How would the AI detect truth or lies, she asked?

AI also allows the police to hide their presence in communities, vastly expanding the pool of people and activities the police can watch. Even simple license plate readers identify hundreds of plates a minute.

Moreover, some cameras are connected to the internet, opening up a possibility for hacker activity.

Worse, some [cameras] are leaking sensitive data about vehicles and their drivers and many have weak security protections that make them easily accessible, Tech Crunch writes.

Joh noted that legal rulings already have given a green light to wider law enforcement use of the cellphone location technology.

In Carpenter v. United States, the Supreme Court in 2018 ruled the FBI was able to access the defendants location through cell phone records that showed over 12,000 pings around the time of a robbery, without requiring a warrant.

Even though Carpenters case is not explicitly about AI, it hits notes that are relevant to privacy and information gathering.

The Court was concerned about tools that had extended beyond augmenting the sensory faculties bestowed upon [the police] at birth, Joh explained.

Automated, third-party information-gathering by police challenges traditional notions of privacy, she wrote.

The conventional view is that no matter whether the government has taken one of a thousand snapshots of your face, you have given up your privacy rights, wrote Joh.

The author concludes with a quote from the Carpenter ruling: Unlike the nosy neighbor who keeps an eye on comings and goings, the technology used by the police was ever alert, and [its] memory is nearly infallible.

Courts and civil liberties groups will therefore need to confront a worrying new reality, the paper said.

[The] artificial intelligence tools being adopted by police departments.. are cheap, powerful, ubiquitous, automated and invasive of privacy in ways that are novel and alarming, warned Joh.

See also: CA License Plate Reader Doesnt Protect Privacy

The full paper can be accessed here.

This summary was prepared by Andrea Cipriano, a TCR staff writer.

See more here:

Police Use of Artificial Intelligence Poses 'Alarming' Threats to Privacy: Paper - Crime Report

These are the jobs that robots are taking over. Robots take retail. Headlines such as these have become so common, theyre practically accepted as fact. While many are quick to blame advancing technology such as artificial intelligence, the real problem is how that technology is deployed in the workplace along with who stands to benefit from it.

Though tech hubs such as San Francisco, Boston and Seattle routinely grab the limelight, Houston too is on the forefront of an innovation that could drastically change the lives of some workers. Starting last year, a robotics company based in Silicon Valley, Nuro, has been using the suburbs of Houston to test its autonomous grocery delivery service.

In this age of driverless cars, were spending less time celebrating the freedom technology brings and more time worried about what it means for those such as the gig economy workers who deliver groceries who will eventually be replaced by autonomous vehicles.

These concerns are legitimate. Just as urgent is the need to grapple with how we can deploy this new technology to benefit workers. In short, the economic benefits of technology should be broadly shared among all of us.

How technological change is implemented, who benefits and who pays a price, will be based on choices that we make as a society. What scholars are learning, unfortunately, is that high economic inequality is confining the benefits of technological progress and accompanying economic growth primarily to the very rich.

Economic inequality the differences between the top 1 percent and the rest of us has been growing in the United States since the 1980s and stands at its highest point in a century. Houston is not immune: In 2015, the Houston metropolitan area ranked seventh among nearly one thousand metropolitan areas in its share of people who reside in the top 1 percent of incomes nationwide, according to a recent study by the Economic Policy Institute.

Technological progress, while making many workers more productive and adding high-skill jobs to the economy, also reinforces economic and other kinds of inequality, such as by race and gender. Technology has contributed to the rise of independent contractors, franchises and the gig economy. These trends have undermined their bargaining power to obtain wage increases and improved conditions.

Though it might be difficult to predict where technology will take jobs and employment in the decades ahead, we can make policy changes today that address inequality and ensure that workers are treated fairly and can earn their share of the productivity benefits technological advancement provides.

A fundamental step to reducing inequality is to ensure that our economy remains competitive and that the first mover advantage to create new platforms doesnt calcify into monopolies that stifle future innovation and entrepreneurship. Our 21st-century policies must be up to the task of ensuring market competition in the face of new technologies.

We also need to ensure that the gains of growth are shared. We have an easy way to do this: put in place a tax code that does not fossilize wealth into the hands of few. Changes in recent years have mostly benefited the wealthy and corporate interests, not the many. We need a tax code that gives us the capacity to make much-needed investments in our communities and our people that will ensure our economy can be competitive for generations to come. A number of proposals for taxing wealth have been offered; though some go farther than others, any step is a step in the right direction.

And, to directly support the workers who must contend with changing technologies, we need to modernize labor laws and other policies affecting workers to account for the changes taking place in the economy and to reverse actions that have weakened labor unions and worker power. The federal labor standards enacted in the 20th century essentially do not exist for millions of gig workers and others. Those standards for safety, for wages, for working conditions should be updated to meet the needs of todays families by including things like paid leave and extended to all.

In addition, workers voices need to be heard in the workplace. Worker input can lead to greater equity and more efficient production processes. See Harvard Universitys Labor and Worklife Program, which recently issued the Clean Slate for Worker Power, an agenda of policy recommendations that would strengthen the ability of organized labor to rebalance the power between workers and employers.

Luckily Houston has already begun to take action. In 2017, the Mayoral Task Force on Equity produced an in-depth report with a series of recommendations for addressing inequality in Houston. The policies included in Rising Together: A Roadmap to Confront Inequality in Houston ranged from a new jobs program and early childhood education reforms to greater investment in low-income neighborhoods and a more progressive tax system.

Too many conversations about technology and the future of work start from the premise that technology controls us, and not the other way around. If we want to ensure that technology serves all of us and that its benefits are broadly shared then we need to address inequality so that workers are better positioned to weather any challenges the robots might bring.

Boushey is the president and CEO of the Washington Center for Equitable Growth. She will be speaking about her book "Unbound: How Inequality Constricts Our Economy and What We Can Do About It" at Rice University on Wednesday, Feb. 12, at 6:30 p.m. This event is free and open to the public but registration is recommended. She will also be presenting at a Rice Scientia Conference on Work in the 21st Century: Automation, Workers, and Society Feb 13-14.

Follow this link:

Robots and artificial intelligence can benefit workers instead of hurting them if we address inequality today [Opinion] - Houston Chronicle

WASHINGTON, February 13, 2020 Biased artificial intelligence poses obstacles for marginalized communities when trying to access financial services like applying for a mortgage loan, said panelists speaking before the House Committee on Financial Services.

In a statement before the committee on Wednesday, privacy and AI advisor Br A. Williams wrote, Data sets in financial services are used to determine home ownership and mortgage, savings and student loan rates; the outcomes of credit card and loan applications; credit scores and credit worthiness, and insurance policy terms.

In practice, biased AI could mean that black homeowners were confined to specific areas of a city and that their credit worthiness led to higher interest rates, Williams said.

Rayid Ghani, of the Machine Learning Department at Carnegie Mellon Universitys Heinz College of Information Systems and Public Policy, said that it is not enough to create an equitable AI. Rather, there needs to be equity across the entire decision-making process.

Machine bias is not inevitable, nor is it final, concurred Brookings Institution Fellow Makada Henry-Nickie.

This bias though, is not benign. AI has enormous consequences for racial, gender, and sexual minorities, said Henry-Nickie.

University of Pennsylvania Professor Michael Kearns said biased AI is generally not the result of human malfeasance, such as racist or incompetent software developers.

However, Williams argued that if AI is being fed historical data, its already biased.

In order to create an equal AI system, Ghani included steps to an equitable process in the actual construction of AI. Ghani suggested:

See original here:

Biased Artificial Intelligence has Sinister Consequences for Marginalized Communities, Argue Panelists - BroadbandBreakfast.com

This report presents the worldwide Artificial Intelligence Robotics market size (value, production and consumption), splits the breakdown (data status 2018 and forecast to 2025), by manufacturers, region, type and application.

This study also analyzes the market status, market share, growth rate, future trends, market drivers, opportunities and challenges, risks and entry barriers, sales channels, distributors and Porters Five Forces Analysis.

The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market.

Request Sample Report @ https://www.marketresearchhub.com/enquiry.php?type=S&repid=2473615&source=atm

Top Companies in the Global Artificial Intelligence Robotics Market:

In global market, the following companies are covered: NVIDIAIntelIBMMicrosoftXilinxSoftbankHanson Robotics

Market Segment by Product TypeService RobotsIndustrial Robots

Market Segment by ApplicationMilitary & DefenseLaw EnforcementHealthcare AssistanceEducation and EntertainmentPersonal Assistance and CaregivingStock ManagementOthers

Key Regions split in this report: breakdown data for each region.United StatesChinaEuropean UnionRest of World (Japan, Korea, India and Southeast Asia)

Make An EnquiryAbout This Report @ https://www.marketresearchhub.com/enquiry.php?type=E&repid=2473615&source=atm

The report provides a valuable source of insightful data for business strategists and competitive analysis of Artificial Intelligence Robotics Market. It provides the Artificial Intelligence Robotics industry overview with growth analysis and futuristic cost, revenue and many other aspects. The research analysts provide an elaborate description of the value chain and its distributor analysis. This Tire Artificial Intelligence Robotics study provides comprehensive data which enhances the understanding, scope and application of this report.

Influence of the Artificial Intelligence Robotics market report:

-Comprehensive assessment of all opportunities and risk in the Artificial Intelligence Robotics market.

Artificial Intelligence Robotics market recent innovations and major events.

-Detailed study of business strategies for growth of the Artificial Intelligence Robotics market-leading players.

-Conclusive study about the growth plot of Artificial Intelligence Robotics market for forthcoming years.

-In-depth understanding of Artificial Intelligence Robotics market-particular drivers, constraints and major micro markets.

-Favorable impression inside vital technological and market latest trends striking the Artificial Intelligence Robotics market.

You can Buy This Report from Here @ https://www.marketresearchhub.com/checkout?rep_id=2473615&licType=S&source=atm

The report has 150 tables and figures browse the report description and TOC:

Table of Contents

1 Study Coverage

1.1 Artificial Intelligence Robotics Product

1.2 Key Market Segments in This Study

1.3 Key Manufacturers Covered

1.4 Market by Type

1.4.1 Global Artificial Intelligence Robotics Market Size Growth Rate by Type

1.4.2 Hydraulic Dredges

1.4.3 Hopper Dredges

1.4.4 Mechanical Dredges

1.5 Market by Application

1.5.1 Global Artificial Intelligence Robotics Market Size Growth Rate by Application

2 Executive Summary

2.1 Global Artificial Intelligence Robotics Market Size

2.1.1 Global Artificial Intelligence Robotics Revenue 2014-2025

2.1.2 Global Artificial Intelligence Robotics Production 2014-2025

2.2 Artificial Intelligence Robotics Growth Rate (CAGR) 2019-2025

2.3 Analysis of Competitive Landscape

2.3.1 Manufacturers Market Concentration Ratio (CR5 and HHI)

2.3.2 Key Artificial Intelligence Robotics Manufacturers

2.3.2.1 Artificial Intelligence Robotics Manufacturing Base Distribution, Headquarters

2.3.2.2 Manufacturers Artificial Intelligence Robotics Product Offered

2.3.2.3 Date of Manufacturers Enter into Artificial Intelligence Robotics Market

2.4 Key Trends for Artificial Intelligence Robotics Markets & Products

3 Market Size by Manufacturers

3.1 Artificial Intelligence Robotics Production by Manufacturers

3.1.1 Artificial Intelligence Robotics Production by Manufacturers

3.1.2 Artificial Intelligence Robotics Production Market Share by Manufacturers

3.2 Artificial Intelligence Robotics Revenue by Manufacturers

3.2.1 Artificial Intelligence Robotics Revenue by Manufacturers (2019-2025)

3.2.2 Artificial Intelligence Robotics Revenue Share by Manufacturers (2019-2025)

3.3 Artificial Intelligence Robotics Price by Manufacturers

3.4 Mergers & Acquisitions, Expansion Plans

More Information.

Continued here:

Artificial Intelligence Robotics Market: Drivers, Restraints, Opportunities, and Threats 2019-2029 - Instant Tech News

This has long been a staple of my collection of QTWTAIN Questions To Which The Answer Is No. Originally the question took the form of headlines such as, Will robots replace human journalists? A few years ago, the questions became more insistent as some news organisations experimented with automating sports results or market reporting.

The answer was still always No. Most journalism is a form of conversation. While it is possible to imagine weather reporting or traffic updates being handled by software, writing news stories or comment articles is a form of Turing test that computers are still a long way from passing.

Even so, artificial intelligence is capable of some amazing things. One of the big advances in technology recently has been in voice recognition software. Many journalists, including me, now use a programme called Otter.ai (the ai stands for artificial intelligence), which converts audio recordings into text.

Sharing the full story, not just the headlines

The rest is here:

Editor's Letter: Will artificial intelligence put journalists out of work? - The Independent

Digital agency space150 created a deepfake version of the rapper named Travisbott.

Recent advances in machine learning have allowed musicians like Holly Herndon to use artificial intelligence programs while creating their music. As reported in Adweek, digital agency space150 recently pushed the technology to its limits by creating an entirely AI-generated song with lyrics and melodies modeled after Travis Scotts music.

After two weeks of feeding lyrics into a text generator model, the creative team produced a track titled Jack Park Canny Dope Man by a deepfake version of the rapper named Travisbott. It was released with an unsettling music video:

The track comes complete with Scotts signature its lit and straight up ad-libs and features heavily auto-tuned vocals with nonsensical rhymes:

I aint got the surfers cause I know Im not that hardBut I got all my old bitches mad by the barsThinkin at the Grammys, in the family, I got starsTry to put in the plane, but the blame be on the cars

Ned Lampert, executive creative director at space150, explained to Adweek why the agency created the project, which wasnt designed for any particular client.

We were sort of fascinated with like, What if we tried to make a songlike an actual good songby using AI and basically creative directing AI? he said. And so we chose Travis Scott just because he is just such a unique artist and he has a unique sound and everything sort of has an aesthetic to it, both audibly and visually.

According to Lampert, the bot initially kept generating lyrics about food while it was still learning to mimic the Houston rappers style. There was one line like, I dont want to fuck your party food, he recalled.

Much like Herndon did with her 2019 album, PROTO, the agency used neural network programs to create the melodies and percussion arrangements for the songs instrumental, which falls just short of approximating the feel of Travis' signature sound.

In late 2019, Canadian musician Grimes spoke about AIs growing capacity to create music on the Mindscape podcast. Once theres actual AGI (Artificial General Intelligence), its gonna be so much better at making art than us, she said. Once AI can totally master science and art, which could happen in the next 10 years, probably more like 20 or 30 years.

While Travisbott shows machine learning hasnt surpassed human ability quite yet, AI-generated music continues to improve at a rapid pace.

Check out the full Adweek report here, and read all the lyrics to TravisBotts Jack Park Canny Dope Man on Genius now.

View original post here:

This Fake Travis Scott Song Created By Artificial Intelligence Sounds Almost Like The Real Thing - Genius

Artificial Intelligence (AI) to be $100 billion sector by 2025

AI startups received $14 billion investment in 2019

AI, an effective tool for Indian Judiciary System : CII Summit and Expo on AI Application & Digi-Tech

Day two ofConfederation of Indian Industrys (CII)Summit and Expo on AI Application & Digi-Tech,kick started with a thought-provoking panel discussion onAI in Public Service.The session highlighted the benefits of AI interventions in Agriculture, Smart Cities, Healthcare, Skilling, Education, Public Utility Services, Judiciary and Governance.

Mr. Sameer Dhanrajani, CEO, AIQRATEsaid that in India we are seeing a great opportunity for AI to support various processes both in the public and private entities. One of the areas where AI can be most effective is in the countrys judicial system. Currently we have 33 million legal cases pending in India. 84% of which has an average pendency of 13 years. AI can be used to deal with all previous cases that we have in our repository by extrapolating it by means of text-mining, multilayer perceptron (MLP) and deep learning. Leaving the legal system to focus on their core job, which is to solve and close cases on an agile basis.

Globally, AI has seen $45 to $58 billion investment during the last year. It is growing at the fastest pace of any exponential technology. The AI segment will be worth over $100 billion by 2025. This gives ample indication of the scale and opportunities in this sector. According to Mr. Dhanrajani, the companies that have adopted AI will take away $1.2 trillion worth of business from their competitors. In 2019 alone AI startups have received $14 billion investment across 600 funding events.

Realizing the importance of AI currently, 28 nations around the world are curating or drafting AI policies and strategies. India is one among them however where the country lags behind is in research. In India we have only 2000 to 2500 research papers submitted every year and China has 10 times more. Out of 34.8 million students coming out of our higher education system in the country only 18% are employed. The job opportunities in the new age will require skills that are not taught in our educational system and this needs to change.

India is uniquely poised to be a global leader in AI, and this is due to the diversity of our population generating a diverse set of data. Attaining a premier position in AI will require convergence of all stakeholders. Towards this, India need to focus on 3 broad areas i.e.Education infusing new age courses and adapting personalized learning powered by AI,Enable create an open innovation platform, a pipeline of AI centric solutions and their adoption andEthics Draft an operating framework within which AI can be developed, Mr. Dhanrajani elaborated.

The panel discussion highlighted the sectors in India where AI can make the most difference:

Governance AI can power several governance initiatives ranging from security threats, RTI, potential fraud and corruption to improving the legal system, curbing human trafficking and tracking of missing persons.

Ms.AparnaGupta,Analytics&DataScienceLeader,OracleCloudSolutionsHub;MrKapilGandhi,VicePresidentStrategyIntelligentAutomation,GenpactDigital;Ms.PadmashreeShagrithaya,VicePresident&HeadAnalytics,DataScienceandVisualization, Capgemini;MrSanjeevKumar,SrDirectorData&Analytics, BakerHughes;MrSatyamoyChatterjeeExecutiveVicePresident AnalytticaDatalabInc also participated in the panel discussion chaired byMr. Sameer Dhanrajani.

With an objective of identifying and showcasing the best Start-up with the most Innovative scale deployment of Artificial Intelligence & Industrial AI in a large corporate environment CII in association withAccenture Ventures held theCII AI Challenge which felicitated the best startups in each of the segment.

AskSidhas been recognized as the Best Start up for Innovative deployment of Artificial Intelligence in large scale corporate environment.

QualitasTechnologieshas been recognized as the Best Start up for Innovative deployment of Industrial AI in large scale corporate environment.

The summit witnessed a live audience poll for the presentation made by the Start-ups and Orbo.aiwas recognized has Best Start up (Audience poll category ).

More:

Artificial Intelligence to be $100 billion sector by 2025 - CXOToday.com