The EARN IT Act revives the legal war over encryption – Scot Scoop News

The new bill, the EARN IT Act, makes tech companies more liable for what occurs on their platforms, but critics are worried that it could weaken privacy and security on the internet.

Historically, internet companies have not been legally responsible for the content on their service. The hope is that if tech companies are held accountable for abuse on their platforms, they will mitigate it.

But that comes with a catch: if the bill passes, services that utilize effective encryption often to protect users privacy are in legal jeopardy, and likely to weaken their security. It would make it easier for hackers to break into phones and internet connections, reducing the security of internet finance and social media.

Unbreakable cryptography is readily available in the modern world, but it has not always been that way. The United States government and its allies have long fought to keep secure encryption from the public, partly through restricting the export of encryption.

In his 1996 book, Applied Cryptography, Bruce Schneier wrote, According to the U.S. government, cryptography is a munition. This means it is covered under the same rules as a TOW missile or an M1 Abrams Tank. If you sell cryptography overseas without the proper export license, you are an international arms smuggler.

With those restrictions, the U.S. was trying to prevent hostile governments from using unbreakable encryption. But law enforcement was also trying to keep cryptography out of the hands of U.S. citizens. In 1993, the Clinton Administration proposed the Clipper Chip, which, in theory, would have prevented criminals from eavesdropping on phone calls, but still allowed the government to listen in. In practice, however, the clipper chip had vulnerabilities that allowed anyone to disable the part of the chip that allowed government access. Phone manufacturers did not implement it, and by 1996 it was defunct.

Tech companies state that they cannot assure privacy for their users while building a flaw in their security that allows law enforcement to access user data.

Matt Blaze, the computer scientist who broke the clipper chip, said, When I hear If we can put a man on the moon, we can do this, it is like saying If we can put a man on the moon, well surely we can put a man on the sun.

In 1996, the U.S government passed the Communications Decency Act. Section 230 of that law states that no provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider. This gives tech companies legal protection against abuse on their platforms. However, the EARN IT Act would make companies have to earn this protection by following the best practices.

What worries critics of the bill is that those best practices are determined by a commission dominated by law enforcement.

The Electronic Frontier Foundation, an internet freedom advocacy organization partially responsible for the widespread use of secure encryption,said in their statement on the EARN IT Act, We know how [Attorney General William Barr] is going to use his power on the best practices panel: to break encryption.

While the bill brings harsh criticism from the tech industry and advocates for free speech on the internet, it has bipartisan support.

This bill is a major first step. For the first time, you will have to earn blanket liability protection when it comes to protecting minors. Our goal is to do this in a balanced way that doesnt overly inhibit innovation, but forcibly deals with child exploitation, said Republican Sen. Lindsay Graham, who co-sponsored the bill with Democrat Richard Blumenthal.

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The EARN IT Act revives the legal war over encryption - Scot Scoop News

Three things central bankers can learn from Bitcoin – MIT Technology Review

For central bankers, the game changed last summer when Facebook unveiled its proposal for Libra. Many have responded by seriously exploring whether and how they should issue their own digital money.

Arguably, though, the more fundamental change is more than a decade old. It was Bitcoin that first made it possible to transfer digital value without the need for an intermediary, a model that competes directly with the traditional financial system. The networks resilience against attackers suggests there is another way of setting up the system.

Last weekend at the MIT Bitcoin Expo held on campus in Cambridge, Massachusetts, I sat down with experts familiar with central banking as well as cryptocurrency. We discussed the practical concerns central bankers should be considering as they begin to design their own digital money systems. One common theme: central bankers have plenty to learn from Bitcoin.

Sign up for the Chain Letter blockchains, cryptocurrencies, and why they matter

Security can be achieved through resilience.

The US Federal Reserve has no current plans to issue a central bank digital currency (CBDC). But if it ever did, nine out of the top 10 requirements would pertain to security, said Bob Bench, director of applied fintech research at the Boston Fed. Because the second that thing goes live, he said, its the most attacked program in the world.

Bitcoin, with its mix of transparency, cryptography, and economic incentives, has something to teach central bankers about data security, according to Robleh Ali, a research scientist at the MIT Media Labs Digital Currency Initiative. Its a system that exists in a very hostile environment, and its proved to be resilient to that, said Ali. Its also a fundamentally different way of achieving security compared with how it is done in the traditional system: Rather than try to hide the data behind walls, its trying to make the system so its inherently resilient.

Keep it simple.

CBDCs can be thought of as third-generation digital currencies, said Ali. If Bitcoin is the first generation, Ethereum and other so-called smart-contract platforms, which include relatively complicated programming languages, can be seen as the second generation. While it may be tempting to add even more bells and whistles to a CBDC system, that would be the wrong approach, Ali said, because the more complexity you have, the more opportunities you give attackers to break in. What you want in the third generation is a much simpler system even than Bitcoin, he said. Its more about taking things away than adding things, and I think in terms of making it secure, that should be the mindset.

Privacy is going to be very tricky.

Ali said he expects not all central banks that choose to issue digital currency will use the same system, but many will likely pursue a hybrid between blockchain-based cryptocurrencies like Bitcoin and more traditional, centralized systems.

Such permissioned blockchain systems, also called distributed ledger technologies, could give central banks new tools, like the ability to program the currency to perform specific functions, said Sonja Davidovic, an economist at the International Monetary Fund. For instance, it may let banks automate their responses to certain kinds of economic changes and give central bankers more precise control over the money supply. They would also have much more detailed visibility into the goings-on in their respective economies. Theres a problem, however, said Davidovic: We havent really seen yet how privacy could be protected.

Bitcoin privacy is tricky. Though users are pseudonymous, its public accounting ledger, called the blockchain, makes all transactions traceable. How would a blockchain-based CBDC system keep transaction data private? How would it represent people on the blockchain? Unless the system allows only small transactions, users will have to identify themselves somehow in order to comply with anti-money-laundering rules. How will their identity data be protected from theft, fraud, or even government surveillance?

In the cryptocurrency world, so-called privacy coins like Zcash and Monero, which use advanced cryptographic techniques to hide blockchain transaction data from public view, have arisen as alternatives to Bitcoin. But even if central banks are able to do something similar, it still might be possible to construct profiles of people based on their metadata, said Davidovic: Im not entirely sure that this is a problem that technology alone can solve.

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Three things central bankers can learn from Bitcoin - MIT Technology Review

Only 6% of the ad industry is happy with the digital advertising ecosystem – AdNews

Just 6% of the industry is satisfied with the current digital advertising ecosystem, according to a survey by Industry Index.

The figures come as the Australian Competition and Consumer Commission (ACCC) kicks off two inquiries into online advertising, with one focusing on the adtech industry.

The survey was conducted in partnership with TV advertising solutions company MadHive and AdLedger, a nonprofit research consortium which has members such as Publicis Media, GroupM and OMG.

More than 100 brand marketers, agencies and digital publishers were surveyed, with 6% saying theyre satisfied with the current digital advertising ecosystem. Another 92% believe there is a need for industry-wide standardisation.

Digital advertising is still suffering from the same issues of transparency, fraud and fragmentation, Christiana Cacciapuoti, executive director at AdLedger, says.

And its because we just keep slapping band-aids on a fundamentally broken system, when we need to be developing a new infrastructure thats driven by innovative technologies.

The Australian watchdog is calling for feedback from the industry as it begins its inquiry into the sector, which it has described as opaque. Its expected to hand down its interim report by December.

The adtech ecosystem absolutely needs to be changed, Alysia Borsa, executive vice president and chief business and data officer at Meredith Corporation says.

There is a lack of transparency which leads to fraud, which leads to low quality, which leads to poor performance. Its a really bad cycle.

The survey also found that 83% of respondents believe cryptography can be used to create transparencies and efficiencies, most often agreeing that cryptography could improve problems associated with fraud (66%) and the ability to track results (66%).

Sooner or later, the industry is going to realise that this dysfunctional relationship has got to end, and the only way to fix it is with next-generation technologies, MadHive CEO Adam Helfgott says.

And with blockchain and cryptography already weeding out fraud and solving similar issues on OTT, its only a matter of time till the industry stands together and overhauls the system.

Have something to say on this? Share your views in the comments section below. Or if you have a news story or tip-off, drop us a line at adnews@yaffa.com.au

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Big B and Priyanka Gandhis corona advice, Italy gets freebies & WHO let the dogs out – ThePrint

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New Delhi: Crashing stock markets, free porn and lots of advisories Twitter captures the global rollercoaster that coronavirus has caused.

First, another high profile coronavirus case: Canadian Prime Minister Justin Trudeau informed Twitter that his wife had tested positive for and is now in quarantine.

Former Congress president Rahul Gandhi slams the Modi government, again and its not the economy

His sister Priyanka, meanwhile, lectures us on keeping safe in these challenged times.

While Twitter talks about globalisations role in the spread of coronavirus, author Kavitha Rao shares a different, witty perspective.

Actions speak louder than words, and superstar Amitabh Bachchan is doing just that. Check out his advice

Theres good news from WHO for our best friend on COVID-19 and author Liam Hackett has something delightful to say about that.

Writer Rupa Gulab finds something funny in these pandemic times.

Actor Tom Hanks offers a thank you note to all those who wished his wife and him a speedy recovery from coronavirus.

Dont worry, Hanks, we know whos the stronger one in this battle!

Amidst all the conspiracy theories about which country might have engineered COVID-19 and why, Chinese foreign ministry spokesperson Zhao Lijian offers his version

The world might be facing a massive shutdown but at least the Italians are being granted some interesting freebies Ahem.

Discover why US whistleblower Edward Snowden contemplates investing in cryto-currency.

Finally, Farooq Abdullahs daughter Safia Abdullah Khan took to Twitter to celebrate her fathers release from detention in the Valley today.

-Inputs by Yimkumla Longkumer

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What is social distancing? And what does it have to do with COVID-19? – Deseret News

SALT LAKE CITY Just a couple of months ago, few people outside of science and emergency preparedness had ever used the term social distancing. But Americans were doing it already, in an incremental yet revolutionary change enabled by technology.

We distanced ourselves from other people when we checked ourselves in at an airport kiosk or checked ourselves out at the grocery store. We became a little more socially distant once we stopped pulling over and asking for directions because we had GPS in our cars. We began eating restaurant food without going to restaurants (thanks to DoorDash and Uber Eats), and we watch movies on big screens at home, instead of seeing them with our neighbors in crowded theaters.

In short, even before COVID-19, America had been preparing for coronavirus-driven social distancing for years.

Facebook founder Mark Zuckerberg famously said that his companys goal was to bring people closer together. British economist Frances Cairncross said technology promised the death of distance.

But the togetherness of technology, which allows an increasing number of Americans to work remotely as the new coronavirus spreads, is a different kind of togetherness than what families enjoy at the dinner table, or the banter shared at an office or coffee shop. It also comes at a cost.

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As author John Horvat wrote, Commerce is based on more than just transactions. It has always relied upon organic relationships.

The pleasantries exchanged at the cash register do more than pass time, Horvat said. These seemingly minor exchanges help knit communities together. They tend to produce what sociologists call social capital.

As Americans retreat even further from each other out of fear of contracting COVID-19, we will likely experience more of the negative effects of the social distancing weve already been doing, including loneliness and depression, sociologists and other experts say.

But in this case, there could be a benefit once the pandemic has passed: This mandatory social distancing might be the catalyst that brings us closer together again.

The rapid spread of the new coronavirus, which emerged in Wuhan, China, in late 2019, is enabled, in part, because of how long it takes for symptoms to occur (five days or longer) and because it can be transmitted from one person to another within a space of about six feet, according to the Centers for Disease Control and Prevention.

While people are most contagious when they are sick, medical experts believe that transmission can also occur before symptoms emerge, which is why governments across the world were calling for social distancing measures weeks before the World Health Organization on March 11 declared the coronavirus to be a pandemic.

The term social distancing itself isnt new.

A report prepared 10 years ago by the Association of State and Territorial Health Officials, in conjunction with the CDC, deemed social distancing an effective nonpharmaceutical intervention to combat pandemics and argued that the practice was effective during the flu pandemic of 1918-19.

Then, the social distancing ordered by the city of St. Louis, Missouri, stood in stark contrast to that of Philadelphia, which held a parade and became the U.S. city with the greatest number of deaths, 16,000 in six months.

More than a century later, Philadelphia is still being punished for this on Twitter, where people are writing Dont be Philadelphia; be St. Louis.

To be St. Louis nationwide, health officials are urging Americans to take a drastic and unsettling step: to stay home as much as possible. Cancel everything. Now, Yascha Mounk, an assistant professor at Johns Hopkins University, wrote in The Atlantic.

For introverts, the overly stressed and people who are uncomfortable in crowds, remote work and widespread cancellations may sound like a vacation, government permission to do what they yearn to do anyway. Ive been ahead of the curve. Ive been socially-distancing myself for the past 20 years, Fox News personality and comedian Greg Gutfeld posted on Twitter. And National Security Agency whistleblower Edward Snowden, now living in Russia, posted on Wednesday, Social distancing is underrated.

The idea of social distancing can seem like an anomaly in an age of hyper-connectivity, said Dan Rothwell, professor emeritus of communication at Cabrillo University in Aptos, California.

But as Rothwell points out in his book In Mixed Company: Communicating in Small Groups and Teams, virtual connection has resulted in a society-wide erosion of civility.

Research has shown that virtual interaction is more likely to be negative and disapproving than when people communicate face to face, and social distance can promote misunderstandings, Rothwell said.

Moreover, the ease with which technology allows us to retreat, even from our own family members, is troubling, he added.

My next-door neighbor is my daughter, her husband and our four grandkids. Its wonderful, but I cant tell you the number of times weve texted to see if theyre there, or picked up the phone to ask one of the grandkids to send some milk over to us, when what would have happened before is we would have had to wander over there and knock on the door.

That has happened in offices, as well, as researchers have found that people who work near each other will text instead of getting up and walking over to anothers desk to ask a question. And one study has shown that nearly 7 in 10 millennials have been told via text or Facebook that a romantic relationship was over, Rothwell said.

That said, technology is also making social distancing and quarantine more bearable than it was in centuries past, when being banished from a community, as for leprosy, meant you might never see your family again.

We can quarantine ourselves and still be connected. And thats an interesting contradiction, Rothwell said.

Some people arent bothered by health officials recommendation that we keep close to our homes like the person who responded to Snowden on Twitter, Its times like these I appreciate my social anxiety and hermit-like tendencies.

Although social distancing may be easier for introverted people than extroverts, the response to COVID-19 will expose the myth that introverts dont like being around people, said Susan Cain, author of Quiet: The Power of Introverts in a World That Cant Stop Talking.

While introverted people are energized by quiet, theyre not antisocial. They just want to interact quietly and with fewer people at a time, Cain said.

But at a time like this, anyones preferred way of being around people is going to be difficult right now.

And for both introverts and extroverts, too much solitude can morph into loneliness, which is increasing among all age groups in the U.S.

As Claire Pomeroy reported for Scientific American last year, nearly half of Americans say that they frequently feel alone and with no meaningful connection with other people. Loneliness itself has been described as an epidemic.

Biologists have shown that feelings of loneliness trigger the release of stress hormones that in turn are associated with higher blood pressure, decreased resistance to infection and increased risk of cardiovascular disease and cancer, Pomeroy wrote, adding that theres even some evidence that loneliness accelerates cognitive decline.

Although Cain thrives on quiet, she said she likes to write in a busy coffeeshop near her home in the Northeast. She didnt go there on Wednesday, however, because of the coronavirus warnings, and she noticed on Tuesday that it was much less crowded than usual.

I feel like were at a tipping point kind of moment, she said. It has been striking me how much it affects us all, even though it affects us in different ways.

Georganne Bender, a consultant and speaker with Kizer & Bender in St. Charles, Illinois, calls herself a consumer anthropologist because she researches consumer behavior in their natural environment which she still considers to be brick-and-mortar stores. Even though online shopping and speedy delivery was keeping many people at home even before they were told to practice social distancing, she sees pockets of hope.

For example, she cited Wegmans, a chain of grocery stores in the Northeast and Mid-Atlantic states, that offers cafes in some locations, as well as live music, and is creating a sense of community for people who might otherwise be lonely. The first time I went was on a Friday night, and I saw a band playing and people dancing, I was blown away. I saw young couples there, and also men and women there with their elderly parents. When stores do things like that, it does bring people together, and they start making friendships, she said.

Similarly, Matthew Stern reported for RetailWire that a Dutch chain, Jumbo Supermarkets, now has a chatter checkout line for people who want to talk, and a coffee area where lonely shoppers can socialize with volunteers.

Such measures could help combat the isolation of technology-driven societies, Bender said, as well as the negative side effects of social distance, both culturally and government-imposed.

We are growing generations of people who dont know how to communicate, Bender said. Were losing a lot of camaraderie, and knowing your neighbors, how to talk to people, how to make eye contact. But the yearning for interaction still exists even as we retreat into our homes, she said.

You watch people at a conference or trade show, and the interaction is off the charts because were hungry for that, she said.

My hope is that when this is all over and were feeling safe again, we all start coming out of houses and going back to the malls and sporting events and concerts, and having friends over and interacting with each other again. I think were going to be starving for that. And hopefully, the coronavirus isolating us will be a catalyst for people getting back together.

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What is social distancing? And what does it have to do with COVID-19? - Deseret News

Chelsea Manning showed moral strength by choosing imprisonment over collaboration with US govt Snowden – RT

Chelsea Mannings decision to sit in jail rather than cooperate with the US governments prosecution of WikiLeaks is a testament to her character and unwavering principles, NSA whistleblower Edward Snowden has said.

Commenting on Mannings newly-won freedom, Snowden noted that the former Army analyst-turned-whistleblower had been cast into a dungeon by the United States for refusing to work with the government to criminalize the publication of classified materials.

They offered to let her out in exchange for collaboration, but she chose her principles instead.

For Snowden, Mannings unwillingness to exchange her freedom for her beliefs was the ultimate display of moral strength.

Manning was released on Thursday after spending nearly a year in detention for refusing to cooperate with a federal grand jury probe into WikiLeaks. Her release order came shortly after her legal team disclosed that she had been hospitalized after attempting to take her own life.Although no longer locked away in a Virginia detention facility, Manning still faces more than $250,000 in fines for refusing to cooperate with the inquiry.

The ex-army analyst became a household name after leaking hundreds of thousands of documents and files related to the US wars in Iraq and Afghanistan. She was found guilty in 2013 of espionage, and spent four years in prison before her sentence was commuted in 2017.

The decision to release Manning coincides with another legal battle: WikiLeaks co-founder Julian Assange is currently fighting extradition to the United States. The journalist could spend the rest of his life in a US prison if the UK court rules against him.

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ServiceNow pulls on its platforms, talks up machine learning, analytics in biggest release since ex-SAP boss took reins – The Register

As is the way with the 21st century, IT companies are apt to get meta and ServiceNow is no exception.

In its biggest product release since the arrival of SAP revenue-boosting Bill McDermott as new CEO, the cloudy business process company is positioning itself as the "platform of platforms". Which goes to show, if nothing else, that platformization also applies to platforms.

To avoid plunging into an Escher-eque tailspin of abstraction, it is best to look at what Now Platform Orlando actually does and who, if anyone, it might help.

The idea is that ServiceNow's tools make routine business activity much easier and slicker. To this the company is adding intelligence, analytics and AI, it said.

Take the arrival of a new employee. They might need to be set up on HR and payroll systems, get access to IT equipment and applications, have facilities management give them the right desk and workspace, be given building security access and perhaps have to sign some legal documents.

Rather than multiple people doing each of these tasks with different IT systems, ServiceNow will make one poor soul do it using its single platform, which accesses all the other prerequisite applications, said David Flesh, ServiceNow product marketing director.

It is also chucking chatbots at that luckless staffer. In January, ServiceNow bought Passage AI, a startup that helps customers build chatbots in multiple languages. It is using this technology to create virtual assistants to help with some of the most common requests that hit HR and IT service desks, for example password resets, getting assess to Wi-Fi, that kind of thing.

This can also mean staffers don't have to worry where they send requests, meaning if, for example, they've just found out they're going to become a parent, they can fire questions at an agent rather than HR, their boss or the finance team. The firm said: "Agents are a great way for employees find information and abstracts that organizational complexity."

ServiceNow has also introduced machine learning, for example, in IT operations management, which uses systems data to identify when a service is degrading and what could be causing the problem. "You get more specific information about the cause and suggested actions to take to actually remediate the problem," Flesh said.

Customers looking to use this feature will still have to train the machine learning models on historic datasets from their operations and validate models, as per the usual ML pipeline. But ServiceNow makes the process more graphical, and comes with its knowledge of common predictors of operational problems.

Lastly, analytics is a new feature in the update. Users can include key performance indicators in the workflows they create, and the platform includes the tools to track and analyse those KPIs and suggest how to improve performance. It also suggests useful KPIs.

Another application of the analytics tools is for IT teams - traditionally the company's core users - monitoring cloud services. ServiceNow said it helps optimise organisations' cloud usage by "making intelligent recommendations on managing usage across business hours, choosing the right resources and enforcing usage policies".

With McDermott's arrival and a slew of new features and customer references, ServiceNow is getting a lot of attention, but many of these technologies exist in other products.

There are independent robotic process automation (RPA) vendors who build automation into common tasks, while application vendors are also introducing automation within their own environments. But as application and platform upgrade cycles are sluggish, and RPA has proved difficult to scale, ServiceNow may find a receptive audience for its, er, platform of platforms.

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ServiceNow pulls on its platforms, talks up machine learning, analytics in biggest release since ex-SAP boss took reins - The Register

Skill up for the digital future with India’s #1 Machine Learning Lab and AI Research Center – Inventiva

Every tech professional today, irrespective of their role in the organisation, needs to be AI/ML-ready to compete in the new world order. In keeping with the current and future demand for professionals with expertise in AI and Machine Learning (ML), and to help build a holistic understanding of the subject, IIIT Hyderabad, in association with TalentSprint, an ed-tech platform, is offering an AI/ML Executive Certification Program for working professionals in India and abroad.

The programme is designed for working professionals in a 13-week format that involves masterclass lectures, hands-on labs, mentorship, hackathons, and workshops to ensure fast-track learning. The programme is conducted in Hyderabad to enable a wider audience to benefit from the expertise of IIIT Hyderabads Machine Learning Lab.

The programme has successfully completed 11 cohorts with 2200+ participants who are currently working with more than 600 top companies.

You can apply for the 14th cohort here

Participants will get access to in-person classes every weekend. This enables professionals from in and around Hyderabad to build AI/ML expertise from Indias top Machine Learning Lab at IIIT Hyderabad.

With a balanced mix of lectures and labs, the programme will also host hackathons, group labs, and workshops. Participants will also get assistance from mentors throughout the programme. The programmes Hackathons, Group Labs, and Workshops also enable participants to work in teams of exceptional peer groups. Moreover, the lectures are delivered by world class faculty and industry experts.

Refresh your knowledge on coding and the mathematics necessary for building expertise in AI/ML

Learn to translate real-world problems into AI/ML abstractions

Learn about and apply standard AI/ML algorithms to create AI/ML applications

Implement practical solutions using Deep Learning Techniques and Toolchains

Participate in industry projects and hackathons

While there are a number of courses on offer in this domain, what makes this AI/ML Executive Certification Program stand out is the fact that it is offered by Indias No. 1 Machine Learning Lab at IIIT Hyderabad. The programme follows a unique 5-step learning process to ensure fast-track learning: Masterclass Lectures, Hands-on Labs, Mentorship, Hackathons and Workshops. Moreover, participants also get a chance to learn and collaborate with leading people from academia, industry and global bluechip Institutions.

The institute has been the torch bearer of research for several years. It hosts the Kohli Center (KCIS), Indias leading center on intelligent systems. KCISs research was featured in 600 publications and has received 5,792 citations in academic publications. It also hosts the Center for Visual Information Technology (CVIT) that focuses on basic and advanced research in Image Processing Computer Vision, Computer Graphics and Machine Learnin

Tech professionals with at least one year work experience and coding background are encouraged to apply. The programme is especially beneficial for business leaders, CXOs, project managers/developers, analysts and developers. Applications for the 14th cohort are closing on March 20. Apply today!

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Skill up for the digital future with India's #1 Machine Learning Lab and AI Research Center - Inventiva

AI and machine learning is not the future, it’s the present – Eyes on APAC – ComputerWeekly.com

This is a guest post by Raju Vegesna, chief evangelist at Zoho

For many, artificial intelligence (AI) is a distant and incomprehensible concept associated only with science fiction movies or high-tech laboratories.

In reality, however, AI and machine learning is already changing the world we know. From TVs and toothbrushes to real-time digital avatars that interact with humans, the recent CES show demonstrated how widespread AI is becoming in everyday life.

The same can be said of the business community, with the latest Gartner research revealing that 37% of organisations had implemented some form of AI or machine learning.

So far, these technologies have largely been adopted and implemented more by larger organisations with the resources and expertise to seamlessly integrate them into their business. But technology has evolved significantly in recent years, and SaaS (software as a service) providers now offer integrated technology and AI that meets the needs and budgets of small and medium businesses too.

Here are a few evolving trends in AI and machine learning that businesses of all sizes could capitalise on in 2020 and beyond.

The enterprise software marketplace is expanding rapidly. More vendors are entering the market, often with a growing range of solutions, which creates confusion for early adopters of the technology. Integrating new technologies from a range of different vendors can be challenging, even for large enterprise organisations.

So, in 2020 and beyond, the businesses that will make the most of AI and machine learning are the ones implementing single-vendor technology platforms. Its a challenge to work with data that is scattered across different applications using different data models, but organisations that consolidate all its data in one integrated platform will find it much easier to feed it into a machine learning algorithm.

After all, the more data thats available, the more powerful your AI and machine learning models will be. By capitalising on the wealth of data supplied by integrated software platforms, advanced business applications will be able to answer our questions or help us navigate interfaces. If youre a business owner, planning to utilise AI and machine learning for your business in 2020, then the single-vendor strategy is the way to go.

Technology has advanced at such a rate that businesses no longer need to compromise to fit the technology. This type of hyper-personalisation increases productivity for business software users and will continue to be a prime focus for businesses in 2020.

Take, for example, the rise of algorithmic social media timelines we have seen in the last few years. For marketers, AI and machine learning mean personalisation is becoming more and more sophisticated, allowing businesses to supercharge and sharpen their focus on their customers. Companies which capture insights to create personalised customer experiences and accelerate sales will likely win in 2020.

With AI and machine learning, vast amounts of data is processed every second of the day. In 2020, one of the significant challenges faced by companies implementing AI and machine learning is data cleansing the process of detecting, correcting or removing corrupt or inaccurate records from a data set.

Smaller organisations can begin to expect AI functionality in everyday software like spreadsheets, where theyll be able to parse information out of addresses or clean up inconsistencies. Larger organisations, meanwhile, will benefit from AI that ensures their data is more consumable for analytics or prepares it for migration from one application to another.

Businesses can thrive with the right content and strategic, innovative marketing. Consider auto-tagging, which could soon become the norm. Smartphones can recognise and tag objects in your photos, making your photo library much more searchable. Well start to see business applications auto-tag information to make it much more accessible.

Thanks to AI, customer relationship management (CRM) systems will continue to be a fantastic and always-advancing channel through which businesses can market to their customers. Today, businesses can find its top customers in a CRM system by running a report and sorting by revenue or sales. In the coming years, businesses will be able to search top customers, and its CRM system will know what theyre looking for.

With changing industry trends and demands, its important for all businesses to use the latest technology to create a positive impact on its operations. In 2020 and beyond, AI and machine learning will support businesses by helping them reduce manual labour and enhance productivity.

While some businesses, particularly small businesses, might be apprehensive about AI, it is a transformation that is bound to bring along a paradigm shift for those that are ready to take a big step towards a technology-driven future.

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AI and machine learning is not the future, it's the present - Eyes on APAC - ComputerWeekly.com

Navigating the New Landscape of AI Platforms – Harvard Business Review

Executive Summary

What only insiders generally know is that data scientists, once hired, spend more time building and maintaining the tooling for AI systems than they do building the AI systems themselves. Now, though, new tools are emerging to ease the entry into this era of technological innovation. Unified platforms that bring the work of collecting, labelling, and feeding data into supervised learning models, or that help build the models themselves, promise to standardize workflows in the way that Salesforce and Hubspot have for managing customer relationships. Some of these platforms automate complex tasks using integrated machine-learning algorithms, making the work easier still. This frees up data scientists to spend time building the actual structures they were hired to create, and puts AI within reach of even small- and medium-sized companies.

Nearly two years ago, Seattle Sport Sciences, a company that provides data to soccer club executives, coaches, trainers and players to improve training, made a hard turn into AI. It began developing a system that tracks ball physics and player movements from video feeds. To build it, the company needed to label millions of video frames to teach computer algorithms what to look for. It started out by hiring a small team to sit in front of computer screens, identifying players and balls on each frame. But it quickly realized that it needed a software platform in order to scale. Soon, its expensive data science team was spending most of its time building a platform to handle massive amounts of data.

These are heady days when every CEO can see or at least sense opportunities for machine-learning systems to transform their business. Nearly every company has processes suited for machine learning, which is really just a way of teaching computers to recognize patterns and make decisions based on those patterns, often faster and more accurately than humans. Is that a dog on the road in front of me? Apply the brakes. Is that a tumor on that X-ray? Alert the doctor. Is that a weed in the field? Spray it with herbicide.

What only insiders generally know is that data scientists, once hired, spend more time building and maintaining the tools for AI systems than they do building the systems themselves. A recent survey of 500 companies by the firm Algorithmia found that expensive teams spend less than a quarter of their time training and iterating machine-learning models, which is their primary job function.

Now, though, new tools are emerging to ease the entry into this era of technological innovation. Unified platforms that bring the work of collecting, labelling and feeding data into supervised learning models, or that help build the models themselves, promise to standardize workflows in the way that Salesforce and Hubspot have for managing customer relationships. Some of these platforms automate complex tasks using integrated machine-learning algorithms, making the work easier still. This frees up data scientists to spend time building the actual structures they were hired to create, and puts AI within reach of even small- and medium-sized companies, like Seattle Sports Science.

Frustrated that its data science team was spinning its wheels, Seattle Sports Sciences AI architect John Milton finally found a commercial solution that did the job. I wish I had realized that we needed those tools, said Milton. He hadnt factored the infrastructure into their original budget and having to go back to senior management and ask for it wasnt a pleasant experience for anyone.

The AI giants, Google, Amazon, Microsoft and Apple, among others, have steadily released tools to the public, many of them free, including vast libraries of code that engineers can compile into deep-learning models. Facebooks powerful object-recognition tool, Detectron, has become one of the most widely adopted open-source projects since its release in 2018. But using those tools can still be a challenge, because they dont necessarily work together. This means data science teams have to build connections between each tool to get them to do the job a company needs.

The newest leap on the horizon addresses this pain point. New platforms are now allowing engineers to plug in components without worrying about the connections.

For example, Determined AI and Paperspace sell platforms for managing the machine-learning workflow. Determined AIs platform includes automated elements to help data scientists find the best architecture for neural networks, while Paperspace comes with access to dedicated GPUs in the cloud.

If companies dont have access to a unified platform, theyre saying, Heres this open source thing that does hyperparameter tuning. Heres this other thing that does distributed training, and they are literally gluing them all together, said Evan Sparks, cofounder of Determined AI. The way theyre doing it is really with duct tape.

Labelbox is a training data platform, or TDP, for managing the labeling of data so that data science teams can work efficiently with annotation teams across the globe. (The author of this article is the companys co-founder.) It gives companies the ability to track their data, spot, and fix bias in the data and optimize the quality of their training data before feeding it into their machine-learning models.

Its the solution that Seattle Sports Sciences uses. John Deere uses the platform to label images of individual plants, so that smart tractors can spot weeds and deliver pesticide precisely, saving money and sparing the environment unnecessary chemicals.

Meanwhile, companies no longer need to hire experienced researchers to write machine-learning algorithms, the steam engines of today. They can find them for free or license them from companies who have solved similar problems before.

Algorithmia, which helps companies deploy, serve and scale their machine-learning models, operates an algorithm marketplace so data science teams dont duplicate other peoples effort by building their own. Users can search through the 7,000 different algorithms on the companys platform and license one or upload their own.

Companies can even buy complete off-the-shelf deep learning models ready for implementation.

Fritz.ai, for example, offers a number of pre-trained models that can detect objects in videos or transfer artwork styles from one image to another all of which run locally on mobile devices. The companys premium services include creating custom models and more automation features for managing and tweaking models.

And while companies can use a TDP to label training data, they can also find pre-labeled datasets, many for free, that are general enough to solve many problems.

Soon, companies will even offer machine-learning as a service: Customers will simply upload data and an objective and be able to access a trained model through an API.

In the late 18th century, Maudslays lathe led to standardized screw threads and, in turn, to interchangeable parts, which spread the industrial revolution far and wide. Machine-learning tools will do the same for AI, and, as a result of these advances, companies are able to implement machine-learning with fewer data scientists and less senior data science teams. Thats important given the looming machine-learning, human resources crunch: According to a 2019 Dun & Bradstreet report, 40 percent of respondents from Forbes Global 2000 organizations say they are adding more AI-related jobs. And the number of AI-related job listings on the recruitment portal Indeed.com jumped 29 percent from May 2018 to May 2019. Most of that demand is for supervised-learning engineers.

But C-suite executives need to understand the need for those tools and budget accordingly. Just as Seattle Sports Sciences learned, its better to familiarize yourself with the full machine-learning workflow and identify necessary tooling before embarking on a project.

That tooling can be expensive, whether the decision is to build or to buy. As is often the case with key business infrastructure, there are hidden costs to building. Buying a solution might look more expensive up front, but it is often cheaper in the long run.

Once youve identified the necessary infrastructure, survey the market to see what solutions are out there and build the cost of that infrastructure into your budget. Dont fall for a hard sell. The industry is young, both in terms of the time that its been around and the age of its entrepreneurs. The ones who are in it out of passion are idealistic and mission driven. They believe they are democratizing an incredibly powerful new technology.

The AI tooling industry is facing more than enough demand. If you sense someone is chasing dollars, be wary. The serious players are eager to share their knowledge and help guide business leaders toward success. Successes benefit everyone.

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Navigating the New Landscape of AI Platforms - Harvard Business Review