Though police have been using facial recognition technology for the last two decades to try to identify unknown people in their investigations, the practice of putting a majority of Americans into a perpetual photo lineup has gotten surprisingly little attention from lawmakers and regulators. Until now.

Lawmakers, civil liberties advocates and police chiefs have debated whether and how to use the technology because of concerns about both privacy and accuracy. But figuring out how to regulate it is tricky. So far, that has meant an all-or-nothing approach. City Councils in Oakland, California; Portland, Oregon; San Francisco, Minneapolis and elsewhere have banned police use of the technology, largely because of bias in how it works. Studies in recent years by MIT researchers and the federal government found that many facial recognition algorithms are most accurate for white men, but less so for everyone else.

At the same time, automated facial recognition has become a powerful investigative tool, helping to identify child molesters and, in a recent high-profile example, people who participated in the Jan. 6 riot at the Capitol. Law enforcement officials in Vermont want the state’s ban lifted because there “could be hundreds of kids waiting to be saved.”

That’s why a new law in Massachusetts is so interesting: It’s not all or nothing. The state managed to strike a balance on regulating the technology, allowing law enforcement to harness the benefits of the tool while building in protections that might prevent the false arrests that have happened before.

A police reform bill that goes into effect in July creates new guardrails: Police first must get a judge’s permission before running a face recognition search and then have someone from the state police, the FBI or the Registry of Motor Vehicles perform the search. A local officer can’t just download a facial recognition app and do a search.

The law also creates a commission to study facial recognition policies and make recommendations, such as whether criminal defendants should be told that they were identified using the technology.

If you ask lawmakers in the state how they pulled it off, they will frequently refer you to one person: Kade Crockford, an activist at the ACLU of Massachusetts.

“One of my concerns was that we would wake up one day in a world resembling that depicted in the Philip K. Dick novel “Minority Report,” where everywhere you go, your body is tracked; your physical movements, habits, activities and locations are secretly compiled and tracked in a searchable database available to God knows who,” Crockford said.

Two years ago, in June 2019, Crockford and the ACLU of Massachusetts launched a campaign against face surveillance, educating policymakers about problems with the technology and investigating, via public records requests, how widely it was used in the state. That month, the city of Somerville, outside Boston, passed the state’s first ban on government use. It was the second city in the country to do so, after San Francisco the month before.

“We don’t want to play Whac-a-Mole and ban every new dystopic piece of surveillance technology,” said Ben Ewen-Campen, a member of the Somerville City Council. “We want an opt-in dynamic where if society decides they want it, they can have it.”

The ACLU submitted over 400 public record requests to state and federal agencies and found that police regularly used the technology to identify people, usually by running their faces against the state database of driver’s license photos.

One record it received was a September 2015 memo sent by a Massachusetts state police officer to all “local, state and federal law enforcement agencies,” alerting them to a new Registry of Motor Vehicles email address for facial recognition searches. If you didn’t know someone’s identity and wanted to see if their face matched that of a Massachusetts driver, all you had to do was email a photo to that address.

“There was no mention of any policy or legal analysis or legal threshold that law enforcement would have to meet for one of these searches to be performed,” Crockford said.

Emails from local police agencies turned over to the ACLU also revealed that over the last year or so, a number of officers signed up for trial accounts with Clearview AI, an app that searches for someone’s face from billions of photos on the public web.

By 2020, Boston and five more cities in Massachusetts banned government use of facial recognition. State Rep. Dave Rogers, a Democrat who helped to shape the state’s facial recognition bill, said the initiatives by cities and towns helped demonstrate the need for a statewide measure. “We saw that law enforcement was using it in a completely unfettered way,” he said. “Technology in our society is advancing much more rapidly than the law that regulates it.”

A bill passed by the state’s Democratic-controlled legislature banned almost all government use of facial recognition technology, except for the Registry of Motor Vehicles, which uses it to prevent identity theft. The department could run searches for police only with a search warrant. (A warrant is required under a law in Washington state that also takes effect in July.)

But Massachusetts’ Republican governor, Charlie Baker, threatened to veto the measure.

“I’m not going to sign a bill into law that bans facial recognition,” Baker said, according to a local report, citing its use in solving two cases of homicide and child sexual abuse.

Though they were a small part of a larger police reform bill, the facial recognition guidelines attracted attention. NBA player Jaylen Brown and his Boston Celtics teammates submitted an opinion article to The Boston Globe decrying the technology’s racial bias problems and supporting the regulation.

“Despite our positions and profiles as professional athletes, we are not immune to racial profiling and discriminatory policing,” they wrote. “Studies confirm that face recognition surveillance technology is flawed and biased, with significantly higher error rates when used against people of color and women.

“We can’t allow biased technology to supercharge racist policing in the Commonwealth,” they added.

Eventually the legislators and the governor reached a compromise, in the form of the pending regulations.

Some critics, including other ACLU offices, say that facial recognition is uniquely harmful and must be banned. Police unions and the Boston Police Department did not respond to requests for comment. Ryan Walsh, a public information officer with the Springfield, Massachusetts, police department, indicated that the department does not see this measure as the last word on how law enforcement can use this technology.

“While we do not currently use or have plans to use any facial recognition software, we hope the law evolves as the technology evolves and improves,” he said.

Crockford, who has been working on technology and surveillance issues since joining the ACLU of Massachusetts in 2009, said that it was “politically impossible” to ban the use of facial recognition in the state. But she believes that additional guidelines will help prevent abuse and false arrests.

Rogers and state Sen. Cynthia Creem have introduced a new bill with restrictions that include curbs on the use of the technology in public places.

“In our view, this is very much not done,” Crockford said.

Though police have been using facial recognition technology for the last two decades to try to identify unknown people in their investigations, the practice of putting a majority of Americans into a perpetual photo lineup has gotten surprisingly little attention from lawmakers and regulators.

Though police have been using facial recognition technology for the last two decades to try to identify unknown people in their investigations, the practice of putting a majority of Americans into a perpetual photo lineup has gotten surprisingly little attention from lawmakers and regulators. Until now. Lawmakers, civil liberties advocates and police chiefs have debated whether and how to use the technology because of concerns about both privacy and accuracy. But figuring out how to regulate it is tricky. So far, that has meant an all-or-nothing approach. City Councils in Oakland, California; Portland, Oregon; San Francisco, Minneapolis and elsewhere have banned police use of the technology, largely because of bias in how it works. Studies in recent years by MIT researchers and the federal government found that many facial recognition algorithms are most accurate for white men, but less so for everyone else. At the same time, automated facial recognition has become a powerful investigative tool, helping to identify child molesters and, in a recent high-profile example, people who participated in the Jan. 6 riot at the Capitol. Law enforcement officials in Vermont want the state’s ban lifted because there “could be hundreds of kids waiting to be saved.” That’s why a new law in Massachusetts is so interesting: It’s not all or nothing. The state managed to strike a balance on regulating the technology, allowing law enforcement to harness the benefits of the tool while building in protections that might prevent the false arrests that have happened before. A police reform bill that goes into effect in July creates new guardrails: Police first must get a judge’s permission before running a face recognition search and then have someone from the state police, the FBI or the Registry of Motor Vehicles perform the search. A local officer can’t just download a facial recognition app and do a search. The law also creates a commission to study facial recognition policies and make recommendations, such as whether criminal defendants should be told that they were identified using the technology. If you ask lawmakers in the state how they pulled it off, they will frequently refer you to one person: Kade Crockford, an activist at the ACLU of Massachusetts. “One of my concerns was that we would wake up one day in a world resembling that depicted in the Philip K. Dick novel “Minority Report,” where everywhere you go, your body is tracked; your physical movements, habits, activities and locations are secretly compiled and tracked in a searchable database available to God knows who,” Crockford said. Two years ago, in June 2019, Crockford and the ACLU of Massachusetts launched a campaign against face surveillance, educating policymakers about problems with the technology and investigating, via public records requests, how widely it was used in the state. That month, the city of Somerville, outside Boston, passed the state’s first ban on government use. It was the second city in the country to do so, after San Francisco the month before. “We don’t want to play Whac-a-Mole and ban every new dystopic piece of surveillance technology,” said Ben Ewen-Campen, a member of the Somerville City Council. “We want an opt-in dynamic where if society decides they want it, they can have it.” The ACLU submitted over 400 public record requests to state and federal agencies and found that police regularly used the technology to identify people, usually by running their faces against the state database of driver’s license photos. One record it received was a September 2015 memo sent by a Massachusetts state police officer to all “local, state and federal law enforcement agencies,” alerting them to a new Registry of Motor Vehicles email address for facial recognition searches. If you didn’t know someone’s identity and wanted to see if their face matched that of a Massachusetts driver, all you had to do was email a photo to that address. “There was no mention of any policy or legal analysis or legal threshold that law enforcement would have to meet for one of these searches to be performed,” Crockford said. Emails from local police agencies turned over to the ACLU also revealed that over the last year or so, a number of officers signed up for trial accounts with Clearview AI, an app that searches for someone’s face from billions of photos on the public web. By 2020, Boston and five more cities in Massachusetts banned government use of facial recognition. State Rep. Dave Rogers, a Democrat who helped to shape the state’s facial recognition bill, said the initiatives by cities and towns helped demonstrate the need for a statewide measure. “We saw that law enforcement was using it in a completely unfettered way,” he said. “Technology in our society is advancing much more rapidly than the law that regulates it.” A bill passed by the state’s Democratic-controlled legislature banned almost all government use of facial recognition technology, except for the Registry of Motor Vehicles, which uses it to prevent identity theft. The department could run searches for police only with a search warrant. (A warrant is required under a law in Washington state that also takes effect in July.) But Massachusetts’ Republican governor, Charlie Baker, threatened to veto the measure. “I’m not going to sign a bill into law that bans facial recognition,” Baker said, according to a local report, citing its use in solving two cases of homicide and child sexual abuse. Though they were a small part of a larger police reform bill, the facial recognition guidelines attracted attention. NBA player Jaylen Brown and his Boston Celtics teammates submitted an opinion article to The Boston Globe decrying the technology’s racial bias problems and supporting the regulation. “Despite our positions and profiles as professional athletes, we are not immune to racial profiling and discriminatory policing,” they wrote. “Studies confirm that face recognition surveillance technology is flawed and biased, with significantly higher error rates when used against people of color and women. “We can’t allow biased technology to supercharge racist policing in the Commonwealth,” they added. Eventually the legislators and the governor reached a compromise, in the form of the pending regulations. Some critics, including other ACLU offices, say that facial recognition is uniquely harmful and must be banned. Police unions and the Boston Police Department did not respond to requests for comment. Ryan Walsh, a public information officer with the Springfield, Massachusetts, police department, indicated that the department does not see this measure as the last word on how law enforcement can use this technology. “While we do not currently use or have plans to use any facial recognition software, we hope the law evolves as the technology evolves and improves,” he said. Crockford, who has been working on technology and surveillance issues since joining the ACLU of Massachusetts in 2009, said that it was “politically impossible” to ban the use of facial recognition in the state. But she believes that additional guidelines will help prevent abuse and false arrests. Rogers and state Sen. Cynthia Creem have introduced a new bill with restrictions that include curbs on the use of the technology in public places. “In our view, this is very much not done,” Crockford said.

How one US state managed to actually write rules on facial recognition

Where is India in the Artificial Intelligence race? What should India do to be future-ready?

On WION Edit, we will explore these questions.

At the outset, we want to say opposing innovation and science is both silly and futile as Artificial Intelligence is inevitable.

We must equip ourselves for the shift. We would like to highlight an unfortunate contrast here.

Indians have been excellent at Artificial Intelligence, but not India.&nbsp;

Spending on AI has improved in sectors like financial services, high tech, automotive and assembly. But this is far from enough. India's workforce isn't skilled to make the transition.

The vast sections of graduate and post-graduate degree holders view AI as a fantastic idea rather than a realistic one. This utter lack of urgency will prove to be costly.

According to a study by EY and Nasscom, in just 3 years from now, 46 per cent of the workforce will be engaged in entirely new jobs that do not even exist today.

India runs the risk of a huge disruption. Forget AI, the labour force in India is not skilled enough even for conventional jobs in the market..

Job profiles are changing rapidly. If India's young workers are not skilled with relevant technologies, then the jobs data will only look worse by 2022. And don't blame the big business if such a thing happens. Firms will shift to artificial intelligence to cut costs and synergise their functioning.

The workforce has to catch up. Technical education in schools must be enhanced. It's not enough to teach just programming languages like 'Fortran' or 'C' or 'Java'.

Ask yourself this question, how many Indian students use a graphic user interface to visualise materials or chemical structure. India's education system has not evolved. It's just a good old textbook.

That's where the government comes in, revamp education, reskill the workforce. The corporate sector will have to pitch in.

Indians do some of the most difficult research and analysis in computation, coding and theoretical computer science. But for most Indians, the greatest technological break-through over the last 3 decades has been the access to a smartphone!

This divide needs to be corrected if we have to ride the Artificial Intelligence tide and make no mistake, we have to, saying no to evolution is not an option. Preparing for it is.&nbsp; 
&nbsp;

(Disclaimer: WION Edit is the channel's take on the big events of the world)

Where is India in the Artificial Intelligence race? What should India do to be future-ready? On WION Edit, we will explore these questions. At the outset, we want to say opposing innovation and science is both silly and futile as Artificial Intelligence is inevitable.

Where is India in the Artificial Intelligence race? What should India do to be future-ready? On WION Edit, we will explore these questions. At the outset, we want to say opposing innovation and science is both silly and futile as Artificial Intelligence is inevitable. We must equip ourselves for the shift. We would like to highlight an unfortunate contrast here. Indians have been excellent at Artificial Intelligence, but not India. Spending on AI has improved in sectors like financial services, high tech, automotive and assembly. But this is far from enough. India's workforce isn't skilled to make the transition. The vast sections of graduate and post-graduate degree holders view AI as a fantastic idea rather than a realistic one. This utter lack of urgency will prove to be costly. According to a study by EY and Nasscom, in just 3 years from now, 46 per cent of the workforce will be engaged in entirely new jobs that do not even exist today. India runs the risk of a huge disruption. Forget AI, the labour force in India is not skilled enough even for conventional jobs in the market.. Job profiles are changing rapidly. If India's young workers are not skilled with relevant technologies, then the jobs data will only look worse by 2022. And don't blame the big business if such a thing happens. Firms will shift to artificial intelligence to cut costs and synergise their functioning. The workforce has to catch up. Technical education in schools must be enhanced. It's not enough to teach just programming languages like 'Fortran' or 'C' or 'Java'. Ask yourself this question, how many Indian students use a graphic user interface to visualise materials or chemical structure. India's education system has not evolved. It's just a good old textbook. That's where the government comes in, revamp education, reskill the workforce. The corporate sector will have to pitch in. Indians do some of the most difficult research and analysis in computation, coding and theoretical computer science. But for most Indians, the greatest technological break-through over the last 3 decades has been the access to a smartphone! This divide needs to be corrected if we have to ride the Artificial Intelligence tide and make no mistake, we have to, saying no to evolution is not an option. Preparing for it is. (Disclaimer: WION Edit is the channel's take on the big events of the world)

WION Edit: Will Artificial Intelligence lead to job losses?

India is embracing the use of artificial intelligence in a confident but steady manner. Government agencies, start-ups and large corporations are applying it to various functions and processes.

Most of the start-up ecosystem is heavily dependent on the use of new technologies including AI to achieve cost and organisational efficiencies. For the start-ups, using the technology is a natural step if not essential.&nbsp;

With good ideas, but low market presence they depend on AI-based insights to expand in the market. Larger organisations, however, are approaching the technologies with more care and caution. Not least because their size often hinders agility to change over to new systems. Such companies are deploying AI for specific functions of new business divisions.

Individuals are more digital these days than most organisations. Without our realisation, basic AI is already managing our personal and work lives through emails, work processes and even entertainment.

However, India hasn’t invested in AI at the scale required. The key recommendation by a NITI Aayog paper on AI includes setting up collaborative structures between academia, government, industry to create AI-based solutions for economic and development challenges.

A three-way collaboration between government, industry and academia is required for India specific challenges. Since many companies don’t have the risk-taking ability to invest in AI-based pilot projects, a structure for collaboration is needed. This can’t be done by the government alone either. The industry has the capital but not the risk-taking ability. The government can take the risk but doesn’t have inherent knowledge.&nbsp;

Academia has the structure but not the talent. Tech companies are innovative, but they don’t always conform to regulation and are often misguided. But someone has to bring them together. Globally several countries are trying to experiment with structures that will allow them to bring the important stakeholders together including citizens.

The report recognises this, “Many countries have instituted dedicated public offices such as Ministry of AI (UAE), and Office of AI and AI Council (UK) while China and Japan have allowed existing ministries to take up AI implementation in their sectoral areas. Not just national governments, but even local city governments have become increasingly aware of the importance and potential of AI and have committed public investments.”

What form can a structure like this take? Can there be a national body that brings everyone together? Will it be a Ministry of AI? India is yet to clarify its thoughts on this. What is clear is that India will need a body, perhaps not a ministry in the way we know it now. What is required is a coordinating and catalysing body that can guide, shape and enable the use of AI.

Some work has already begun with global organisations like the World Economic Forum (WEF) which is trying to get multiple stakeholders to grasp the importance of AI and related technologies. The Centre for Fourth Industrial Revolution (C4IR) is a global hub created by WEF to improve the adoption of new technologies in a sustainable, responsible and collaborative manner, and to minimise their negative effects in the society.

Prime Minister Narendra Modi had launched the C4IR in October. Mumbai will host the centre for India. Other centres are in San Francisco, Tokyo and Beijing. The over 45 global corporate partners and members include Reliance Industries, Salesforce, Wipro, ABB and SAP.

For India, the C4IR has chosen to support and guide the usage of drones, artificial intelligence and blockchain. The private sector is already using technologies but its growth can be impeded if the government policies don’t keep pace.

C4IR is working with NITI Aayog on expanding access to data to accelerate the adoption of artificial intelligence in sectors such as healthcare, education, smart cities &amp; infrastructure, and smart mobility and transportation. The Centre will support the creation of a National Data Marketplace for India through which available data across these different sectors can be collected and integrated for targeted decision making and analyses using artificial intelligence.

In each of these sectors, the information about various dimensions is fragmented across various bodies that capture and store the data. There is virtually no protocol or framework where this data can be annotated, pooled and analysed. C4IR will help bring all relevant stakeholders together to create governance frameworks, systems and processes that will allow government bodies, private sector and individuals to pool such data and be incentivised for their contribution. For example, in the healthcare sector information about diseases, prevention efforts and clinical trials are distributed across various agencies like private hospitals, pharmaceutical companies and government clinics. For smart data analysis, all healthcare data should be created, curated and stored under a common protocol.

Collaborative structures like these have the potential of transforming the way government and private sector collaborate. Technology can bring a strong bond of trust which will be essential for pooling information and applying it in productive ways.

Though AI by itself is an important tool, the changes it will trigger will be much deeper and beneficial for an emerging economy like India.

(This article was originally published on DNA. Read the <a href="https://www.dnaindia.com/analysis/column-india-s-progress-on-artificial-intelligence-route-2698481">original article)</a>

(Disclaimer: The opinions expressed above are the personal views of the author and do not reflect the views of ZMCL)

India is embracing the use of artificial intelligence in a confident but steady manner. Government agencies, start-ups and large corporations are applying it to various functions and processes.

India is embracing the use of artificial intelligence in a confident but steady manner. Government agencies, start-ups and large corporations are applying it to various functions and processes. Most of the start-up ecosystem is heavily dependent on the use of new technologies including AI to achieve cost and organisational efficiencies. For the start-ups, using the technology is a natural step if not essential. With good ideas, but low market presence they depend on AI-based insights to expand in the market. Larger organisations, however, are approaching the technologies with more care and caution. Not least because their size often hinders agility to change over to new systems. Such companies are deploying AI for specific functions of new business divisions. Individuals are more digital these days than most organisations. Without our realisation, basic AI is already managing our personal and work lives through emails, work processes and even entertainment. However, India hasn’t invested in AI at the scale required. The key recommendation by a NITI Aayog paper on AI includes setting up collaborative structures between academia, government, industry to create AI-based solutions for economic and development challenges. A three-way collaboration between government, industry and academia is required for India specific challenges. Since many companies don’t have the risk-taking ability to invest in AI-based pilot projects, a structure for collaboration is needed. This can’t be done by the government alone either. The industry has the capital but not the risk-taking ability. The government can take the risk but doesn’t have inherent knowledge. Academia has the structure but not the talent. Tech companies are innovative, but they don’t always conform to regulation and are often misguided. But someone has to bring them together. Globally several countries are trying to experiment with structures that will allow them to bring the important stakeholders together including citizens. The report recognises this, “Many countries have instituted dedicated public offices such as Ministry of AI (UAE), and Office of AI and AI Council (UK) while China and Japan have allowed existing ministries to take up AI implementation in their sectoral areas. Not just national governments, but even local city governments have become increasingly aware of the importance and potential of AI and have committed public investments.” What form can a structure like this take? Can there be a national body that brings everyone together? Will it be a Ministry of AI? India is yet to clarify its thoughts on this. What is clear is that India will need a body, perhaps not a ministry in the way we know it now. What is required is a coordinating and catalysing body that can guide, shape and enable the use of AI. Some work has already begun with global organisations like the World Economic Forum (WEF) which is trying to get multiple stakeholders to grasp the importance of AI and related technologies. The Centre for Fourth Industrial Revolution (C4IR) is a global hub created by WEF to improve the adoption of new technologies in a sustainable, responsible and collaborative manner, and to minimise their negative effects in the society. Prime Minister Narendra Modi had launched the C4IR in October. Mumbai will host the centre for India. Other centres are in San Francisco, Tokyo and Beijing. The over 45 global corporate partners and members include Reliance Industries, Salesforce, Wipro, ABB and SAP. For India, the C4IR has chosen to support and guide the usage of drones, artificial intelligence and blockchain. The private sector is already using technologies but its growth can be impeded if the government policies don’t keep pace. C4IR is working with NITI Aayog on expanding access to data to accelerate the adoption of artificial intelligence in sectors such as healthcare, education, smart cities & infrastructure, and smart mobility and transportation. The Centre will support the creation of a National Data Marketplace for India through which available data across these different sectors can be collected and integrated for targeted decision making and analyses using artificial intelligence. In each of these sectors, the information about various dimensions is fragmented across various bodies that capture and store the data. There is virtually no protocol or framework where this data can be annotated, pooled and analysed. C4IR will help bring all relevant stakeholders together to create governance frameworks, systems and processes that will allow government bodies, private sector and individuals to pool such data and be incentivised for their contribution. For example, in the healthcare sector information about diseases, prevention efforts and clinical trials are distributed across various agencies like private hospitals, pharmaceutical companies and government clinics. For smart data analysis, all healthcare data should be created, curated and stored under a common protocol. Collaborative structures like these have the potential of transforming the way government and private sector collaborate. Technology can bring a strong bond of trust which will be essential for pooling information and applying it in productive ways. Though AI by itself is an important tool, the changes it will trigger will be much deeper and beneficial for an emerging economy like India. (This article was originally published on DNA. Read the original article) (Disclaimer: The opinions expressed above are the personal views of the author and do not reflect the views of ZMCL)

India’s progress on Artificial Intelligence route

Tech giant Google introduced a new resource called &#39;learn with Google AI&#39; &nbsp;that provides ways to learn about machine learning and how it can be used to solve day to day problems of real life.

Machine learning (ML) is an application of artificial intelligence that provides systems with an&nbsp;ability to automatically learn and improve from experience without being explicitly programmed.

The company announced this through a blog on their site which mentioned. &quot;to help everyone understand how AI can solve challenging problems, we&rsquo;ve created a resource called Learn with Google AI. This site provides ways to learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems. From deep learning experts looking for advanced tutorials and materials on TensorFlow, to &ldquo;curious cats&rdquo; who want to take their first steps with AI, anyone looking for educational content from ML experts at Google can find it here.&#39;&#39;

<div class="ui-state-default" contenteditable="false"><img alt="" draggable="false" src="http://s.wionews.com/photos/untitled%20design%20(26)-20180305103346.jpg" />
<div class="media-description">
Machine learning (ML) is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. (Others)
</div>
<a class="close-mark close-div" href="javascript:void(0)" id="jqclosemark">&times;</a></div>

&#39;Learn with Google AI&#39; also features a crash course for which can be accessed free of cost.

The course call machine learning crash course provides exercises and interactive visualization with instructional videos that anyone can use to learn and practice Machine learning concepts.

The machine learning crash course was first developed for&nbsp;engineers of Google&nbsp;to learn about machine learning use it to further enhance their work in virtual reality for google earth and their other products.

The blog further said that after the success of Machine learning crash course&#39;s success in the company it inspired them to make it available for everyone.

 
&nbsp;

Machine learning provides systems with an ability to automatically learn things without being explicitly programmed

Tech giant Google introduced a new resource called 'learn with Google AI' that provides ways to learn about machine learning and how it can be used to solve day to day problems of real life. Machine learning (ML) is an application of artificial intelligence that provides systems with an ability to automatically learn and improve from experience without being explicitly programmed. The company announced this through a blog on their site which mentioned. "to help everyone understand how AI can solve challenging problems, we’ve created a resource called Learn with Google AI. This site provides ways to learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems. From deep learning experts looking for advanced tutorials and materials on TensorFlow, to “curious cats” who want to take their first steps with AI, anyone looking for educational content from ML experts at Google can find it here.'' Machine learning (ML) is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. (Others) × 'Learn with Google AI' also features a crash course for which can be accessed free of cost. The course call machine learning crash course provides exercises and interactive visualization with instructional videos that anyone can use to learn and practice Machine learning concepts. The machine learning crash course was first developed for engineers of Google to learn about machine learning use it to further enhance their work in virtual reality for google earth and their other products. The blog further said that after the success of Machine learning crash course's success in the company it inspired them to make it available for everyone.

'Learn with Google AI' to teach machine learning for free