Page 2,785«..1020..2,7842,7852,7862,787..2,7902,800..»

Constellation (DAG) Was The Week’s Top Performing Altcoin | – Digital Market News

The concerns said aloud about the general mechanisms of ETH and BTC are one of the reasons for the two assets sideways action in the previous two months. As a result, other competitors have an opportunity for gaining attention. Among them, Constellation (DAG) has stood out in the previous week.

DAG recorded a new all-time high on 10th July, despite the top crypto coins sideways action. It is a protocol that uses an architecture of a guided acyclic graph. The objective is to achieve a consensus that can theoretically scale infinitely.

- Advertisement -

Data from TradingView and Cointelegraph Markets have shown a rally of 353% for DAG prices. It rallied from the 22nd June low point which stood at $0.037 to the new all-time high on 10th July standing at $0.17.

The reasons behind DAGs strong showing include a functioning DEX being released, an expanding global partners list, as well as the highly scalable low-cost transactions offered.

The recent Lattice Exchange (LTX) is an automatic market based on maker DEX. It uses the Hypergraph network of DEX. As a result, it offers an almost zero fee as well as a decentralized network that can scale horizontally. Over the previous few months, LTX token yield farming has been added by the project through Uniswaps liquidity provision. Otherwise, it directly stakes the on LTX for a 155% calculated APY.

- Advertisement -

Notable partnerships in businesses for DAG include the Airforce of the U.S. and Web Services from Amazon. It has also developed partnerships, in the relevant sector, with KuCoin exchange and Chainlink (LINK).

Recently, Ethereum and Bitcoin have been scrutinized heavily for their cost on the environment and high gas fees. As a result, any project offering secure and cheap gas fees with a TPS that can compete can thrive. The recent Stargazer wallet has a Lattice interface. It also allows zero-cost transactions between persons on the network.

- Advertisement -

Read more:
Constellation (DAG) Was The Week's Top Performing Altcoin | - Digital Market News

Read More..

Local band Chess at Breakfast closes career with show at Aggie Theatre The Rocky Mountain Collegian – Rocky Mountain Collegian

Caleb McFadden, singer and guitarist for Chess at Breakfast, performs with guest guitarist Colin Farnsworth during the Farewell World Tour at the Aggie Theatre July 2. (Michael Marquardt | The Collegian)

On Friday, July 2, local bands Chess at Breakfast and People in General played The Aggie Theatrein a performance that showcased the immense growth of both bands throughout their careers.

For headliners Chess at Breakfast, the show was a grand finale to the groups career as a beloved local band. With two separate sets one featuring a compilation of old songs and the other a performance of their most recent and final album, Monsters Are People the show served as a belated album release and a goodbye to fans and supporters.

Among the supporters were opening band People in General, whose members have played alongside Chess at Breakfast several times throughout the span of Chess at Breakfasts roughly five-year career.

People in General opened the show with a theatrical performance of their unreleased song Regal Toucan, sung by lead vocalist and guitarist Abe Dashnaw and supported by a bare-bones riff from bassist Ben Eberle. As the song progressed, more band members entered the stage and began playing, slowly incorporating elements of the bands typical bright, jazzy sound.

As the addition of drums, keys and trombone filled the room, the energy continued to rise with Dashnaws energetic jumps around the stage as they led the band from a funky pop tune to a more chaotic version of the People in General sound, whichfeatured heavy punk undertones.

This punk rock energy remained constant in their performance, adding a new dimension to the clean but eccentric pop sound fans have come to expect.

Were less afraid of (not) being consumable by a large audience and more focused on whats the most fun to play on stage, Dashnaw said.

The bands decision to incorporate styles like hardcore punk, ska and alternative rock was less about reinventing themselves and subverting expectations than it was about allowing themselves to give into the styles influence.

Weve gotten less hesitant to go a more punk route, Dashnaw said. I played in a punk band before People in General, and I really wanted to differentiate the two. Since Ben (Eberle) joined the band, weve realized it sounds way better when we have a bit more bite to the music.

ForEberle, whose musical background started with ska and punk songs, People in Generals progression toward a harder sound was a natural fit with his melodic and upbeat playing.

Although the fusion of jazz and math rock remains most prevalent in the bands music, the show made it clear that the band is continuing to grow and evolve past the boundaries of their math-y jazz pop or jazzy math pop labels.

Opposite of People In Generals performance as an indication of where the band is headed, Chess at Breakfasts double set was more of a reflection on how the bands music has grown over time and led to the production of their final album, Monsters Are People.

With time and exposure weve added tools to our toolbox, said Mike Davis, the bands drummer. With this last album, I think we were working with all the tools we have.

Throughout their career, the band has done the majority of their work independently, from production to graphic design.

Were definitely a D.I.Y. band in all aspects, Davis said.

A common goal throughout Chess at Breakfasts career has been to explore new ideas through their music and not be defined by a singular sound or style, taking inspiration from across genres and fusing them together.

We always want to do new things and change things up; thats been a really big ethos for us, saidCaleb McFadden, vocalist and guitaristfor the group.

The band takes influence from across the musical spectrum, primarily from genres like prog rock, metal, garage punk and anything heavy.

Sonically, were really into punch big punch, big low end, walls of sound contrasted with soft moments and really playing with tension and release, Davis said.

This performance was evidence of the bands use of contrast in their music, exploring strange guitar melodies backed with low, distorted bass.

Chess at Breakfast uses this theme of contrast lyrically in Monsters Are People as well, using the albums set of recurring characters to explore the positive and negative aspects of human behavior and relationships.

We really wanted to highlight the light and dark side of the human mind, McFadden said.

McFadden, who is a primary songwriter for the group, reflected on how his songwriting process has changed over the course of Chess at Breakfasts career, as he began letting symbolism and significance of lyrics emerge after they were written.

Ive found a lot more solace in thinking of weird abstract lyrics and then putting them together and trying to develop meaning after the fact, McFadden said.

McFaddens strange and sometimes surreal lyrics are a major element of the legacy Chess at Breakfast has left behind in the Fort Collins music scene alongside their unique signature sound.

Ive always felt that creating things is a way to immortalize yourself, said Justin Daggett, bassist for Chess at Breakfast. Ive never created anything thats gone to so many people before, and thats been really cool to see.

Max Hogan can be reached at entertainment@collegian.com or on Twitter @macnogan.

Here is the original post:
Local band Chess at Breakfast closes career with show at Aggie Theatre The Rocky Mountain Collegian - Rocky Mountain Collegian

Read More..

The 3rd International Koltanowski Conference on Chess in Education – uschess.org

July 29-30, 2021

Cherry Hill, New Jersey

Sponsored by the US Chess Trust

http://www.USChessTrust.org

2021 Koltanowski Conference on Chess in Education to be Held Just Prior to U.S. Open Chess Championship

The 2021 Koltanowski Conference on Chess in Education will be held July 29-30, 2021, at the Cherry Hill, N.J., Crowne Plaza, where the U.S. Chess Open Championship will be held. The Conference will explore many practical topics. Presenters are eminent in their fields.

Presentations will discuss:

The 2021 Koltanowski Conference on Chess in Education is held in honor of Dr. Tim Redman, founder of the championship Chess Program at The University of Texas at Dallas. Dr.

Redman organized the first (2001) and second (2011) Koltanowski Conferences on Chess in Education.

The 2021 conference will be held in-person with a limited audience. It will be live-streamed online and available for later viewing.

2021 Koltanowski Conference on Chess in Education is sponsored by the U.S. Chess Trust.

For more information, contact:

Al Lawrence, al@uschesstrust.org or Beatriz Marinello, beatriz@uschesstrust.org

For more details go to: http://www.uschesstrust.org

COVID-19 policies apply: Face masks and social distancing will be in effect for the limited audience. If you wish to attend in-person, please fill out this form:

http://www.uschesstrust.org/3rd-international-koltanowski- conference-on-chess-in-education-registration/

Read the original here:
The 3rd International Koltanowski Conference on Chess in Education - uschess.org

Read More..

[Virtual Roundtable] NISTs Proposal on Bias in Artificial Intelligence Roundtable – July 27th, 12:00 pm – 1:00 pm ET – JD Supra

July 27th, 2021

12:00 PM - 1:00 PM ET

The effects of algorithmic and data biases continue to make headlines and erode public trust in artificial intelligence (AI). Recruiting software unfairly discriminates against women and minorities, facial recognition tools used in law enforcement misidentify specific demographic groups, and algorithms for diagnosing and treating diseases perpetuate inequalities.

In an effort to develop a framework for mitigating the risk of bias in AI, the National Institute of Standards and Technology ("NIST") has issued a proposal for identifying and managing bias in AI and is accepting comments on the proposal until September 10, 2021.

Join us on Tuesday, July 27, 2021, for a lively virtual roundtable discussion as we explore the good and the bad in NISTs proposal and the legal implications for businesses using AI tools in their operations. This roundtable will serve as a forum to help companies that are evaluating whether to file comments and what to include in their comments, as well as an opportunity to connect with peers.

We hope to see you then!

AGENDA:

12:00-12:05 p.m. Overview of NISTs Proposal12:05-12:10 p.m. The Good12:10-12:15 p.m. The Bad12:15-1:00 p.m. Peer-to-Peer Discussion with AI Roundtable Participants

WHO SHOULD ATTEND:

General Counsel and other law department leaders, leaders in human resources including Chief Talent/Acquisition Officer, and other organizational leaders such as Chief Information Officers, Chief Compliance Officers and Chief Regulatory Officers (FDA).

To ensure a quality experience for all participants, space will be limited. Registration is complimentary and pre-registration is required.

This roundtable event is only available live and will not be available at a later date.

For questions about the roundtable, please contact Matt Loomis or Dionna Rinaldi.

Members of the media, please contact Piper Hall.

Read more here:
[Virtual Roundtable] NISTs Proposal on Bias in Artificial Intelligence Roundtable - July 27th, 12:00 pm - 1:00 pm ET - JD Supra

Read More..

Which companies are leading the way for artificial intelligence in the medical sector? – Verdict Medical Devices – Medical Device Network

Koninklijke Philips NV and Medtronic Plc are leading the way for artificial intelligence investment among top medical companies according to our analysis of a range of GlobalData data.

Artificial intelligence has become one of the key themes in the medical sector of late, with companies hiring for increasingly more roles, making more deals, registering more patents and mentioning it more often in company filings.

These themes, of which artificial intelligence is one, are best thought of as any issue that keeps a CEO awake at night, and by tracking and combining them, it becomes possible to ascertain which companies are leading the way on specific issues and which are dragging their heels.

According to GlobalData analysis, Koninklijke Philips NV is one of the artificial intelligence leaders in a list of high-revenue companies in the medical industry, having advertised for 578 positions in artificial intelligence, made nine deals related to the field, filed 113 patents and mentioned artificial intelligence five times in company filings between January 2020 and June 2021.

Our analysis classified 13 companies as Most Valuable Players or MVPs due to their high number of new jobs, deals, patents and company filings mentions in the field of artificial intelligence. An additional two companies are classified as Market Leaders and zero are Average Players. Five more companies are classified as Late Movers due to their relatively lower levels of jobs, deals, patents and company filings in artificial intelligence.

For the purpose of this analysis, weve ranked top companies in the medical sector on each of the four metrics relating to artificial intelligence: jobs, deals, patents and company filings. The best-performing companies the ones ranked at the top across all or most metrics were categorised as MVPs while the worst performers companies ranked at the bottom of most indicators were classified as Late Movers.

Alcon Inc is spearheading the artificial intelligence hiring race, advertising for 701 new jobs between January 2020 and June 2021. The company reached peak hiring in May 2020, when it listed 80 new job ads related to artificial intelligence.

Johnson & Johnson followed Alcon Inc as the second most proactive artificial intelligence employer, advertising for 616 new positions. Koninklijke Philips NV was third with 578 new job listings.

When it comes to deals, Koninklijke Philips NV leads with nine new artificial intelligence deals announced from January 2020 to June 2021. The company was followed by Medtronic Plc with four deals and F. Hoffmann-La Roche Ltd with three.

GlobalData's Financial Deals Database covers hundreds of thousands of M&A contracts, private equity deals, venture finance deals, private placements, IPOs and partnerships, and it serves as an indicator of economic activity within a sector.

One of the most innovative medical companies in recent months was Koninklijke Philips NV, having filed 113 patent applications related to artificial intelligence since the beginning of last year. It was followed by Olympus Corp with 31 patents and Alcon Inc with 19.

GlobalData collects patent filings from 100+ counties and jurisdictions. These patents are then tagged according to the themes they relate to, including artificial intelligence, based on specific keywords and expert input. The patents are also assigned to a company to identify the most innovative players in a particular field.

Finally, artificial intelligence was a commonly mentioned theme in medical company filings. Medtronic Plc mentioned artificial intelligence 11 times in its corporate reports between January 2020 and June 2021. Johnson & Johnson filings mentioned it 11 times and Baxter International Inc mentioned it 11 times.

Methodology:

GlobalDatas unique Job analytics enables understanding of hiring trends, strategies, and predictive signals across sectors, themes, companies, and geographies. Intelligent web crawlers capture data from publicly available sources. Key parameters include active, posted and closed jobs, posting duration, experience, seniority level, educational qualifications and skills.

Customised Electro-Pneumatic Control for Medical Applications

28 Aug 2020

Development and Production of Medical Devices and Primary Packaging

28 Aug 2020

Simulation Equipment and Virtual Reality-Enabled Lessons for Medical Students

28 Aug 2020

Read the rest here:
Which companies are leading the way for artificial intelligence in the medical sector? - Verdict Medical Devices - Medical Device Network

Read More..

Artificial Intelligence Is On The Side Of Apes? Tesla-Fame’s AI-Based ETF Sells Facebook, Walmart And Buys AMC – Markets Insider

The Qraft AI-Enhanced US Large Cap Momentum ETF (NYSE:AMOM), an exchange-traded fund driven by artificial intelligence, has sold a majority of its holdings in Facebook Inc. (NASDAQ:FB) and Walmart Inc. (NYSE:WMT), while loading up on shares in AMC Entertainment Inc. (NYSE:AMC).

What Happened: The ETFs latest portfolio after rebalancing in early July showed that the fund has also sold major chunks ofits holdings, or entirely divested,in home retailer Home Depot Inc. (NYSE:HD), software company Adobe Inc. (NASDAQ:ADBE) and chipmaker Texas Instruments Inc. (NASDAQ:TXN).

The fund has a history of accurately predicting the price movements of electric vehicle makerTesla Inc.'s (NASDAQ:TSLA) shares.

The ETF now has online dating services provider Match Group Inc. (NASDAQ:MTCH), cybersecurity solutions company Fortinet Inc. (NASDAQ:FTNT) and auto parts retailer OReilly Automotive Inc. (NASDAQ:ORLY) as its three largest investments.

Match Group has a 3.65% weighting in the AMOM portfolio, followed by Fortinet and OReilly with 3.5% weighting each.

The other two stocks that make up the top five holdings in AMOM include auto parts retailer AutoZone Inc. (NYSE:AZO) with a 3.1% weighting and enterprise technology company Zebra Technologies Corp. (NASDAQ:ZBRA) with 2.7%.

AMC Entertainment has beenadded to the portfolio this month with a 2.34% weighting. The movie theater chain's stock is up 2078% year-to-date thanks to a short squeeze conducted by retail investors that refer to themselves as "apes."

Prior to the rebalancing, the ETF had Facebook, Walmart, Home Depot, Adobe and Texas Instruments as its five largest stock holdings.

See Also: Best Exchange Traded Funds

Why It Matters: AMOM, a product of South Korea-based fintech group Qraft, tracks 50 large-cap U.S. stocks and reweighs its holdings each month. The fund uses AI technology to automatically search for patterns that have the potential to produce excess returns and construct actively managed portfolios.

AMOM has delivered year-to-date returns of almost 15.1%, compared to its benchmark the Invesco S&P 500 Momentum ETF (NYSE:SPMO) which has returned 14.4% so far this year.

The fund said last week that it has surpassed an important milestone of $50 million in assets under management (AUM), an increase of nearly 1,500% from its $4.22 million total in August last year.

Price Action: Match Group shares closed almost 2.8% higher in Fridays trading session at $162.63, while Fortinet shares closed 1.5% higher at $256.81.

OReilly Automotive shares closed 1.7% higher in Fridays trading session at $591.65.

Read Next: 5 ETFs To Watch In The Second Half Of 2021

Photo by Samantha Celera on Flickr

Excerpt from:
Artificial Intelligence Is On The Side Of Apes? Tesla-Fame's AI-Based ETF Sells Facebook, Walmart And Buys AMC - Markets Insider

Read More..

Infrared cameras and artificial intelligence provide insight into boiling – MIT News

Boiling is not just for heating up dinner. Its also for cooling things down. Turning liquid into gas removes energy from hot surfaces, and keeps everything from nuclear power plants to powerful computer chips from overheating. But when surfaces grow too hot, they might experience whats called a boiling crisis.

In a boiling crisis, bubbles form quickly, and before they detach from the heated surface, they cling together, establishing a vapor layer that insulates the surface from the cooling fluid above. Temperatures rise even faster and can cause catastrophe. Operators would like to predict such failures, and new research offers insight into the phenomenon using high-speed infrared cameras and machine learning.

Matteo Bucci, the Norman C. Rasmussen Assistant Professor of Nuclear Science and Engineering at MIT, led the new work,published June 23 inApplied Physics Letters. In previous research, his team spent almost five years developing a technique in which machine learning could streamline relevant image processing. In the experimental setup for both projects, a transparent heater 2 centimeters across sits below a bath of water. An infrared camera sits below the heater, pointed up and recording at 2,500 frames per second with a resolution of about 0.1 millimeter. Previously, people studying the videos would have to manually count the bubbles and measure their characteristics, but Bucci trained a neural network to do the chore, cutting a three-week process to about five seconds. Then we said, Lets see if other than just processing the data we can actually learn something from an artificial intelligence, Bucci says.

The goal was to estimate how close the water was to a boiling crisis. The system looked at 17 factors provided by the image-processing AI: the nucleation site density (the number of sites per unit area where bubbles regularly grow on the heated surface), as well as, for each video frame, the mean infrared radiation at those sites and 15 other statistics about the distribution of radiation around those sites, including how theyre changing over time. Manually finding a formula that correctly weighs all those factors would present a daunting challenge. But artificial intelligence is not limited by the speed or data-handling capacity of our brain, Bucci says. Further, machine learning is not biased by our preconceived hypotheses about boiling.

To collect data, they boiled water on a surface of indium tin oxide, by itself or with one of three coatings: copper oxide nanoleaves, zinc oxide nanowires, or layers of silicon dioxide nanoparticles. They trained a neural network on 85 percent of the data from the first three surfaces, then tested it on 15 percent of the data of those conditions plus the data from the fourth surface, to see how well it could generalize to new conditions. According to one metric, it was 96 percent accurate, even though it hadnt been trained on all the surfaces. Our model was not just memorizing features, Bucci says. Thats a typical issue in machine learning. Were capable of extrapolating predictions to a different surface.

The team also found that all 17 factors contributed significantly to prediction accuracy (though some more than others). Further, instead of treating the model as a black box that used 17 factors in unknown ways, they identified three intermediate factors that explained the phenomenon: nucleation site density, bubble size (which was calculated from eight of the 17 factors), and the product of growth time and bubble departure frequency (which was calculated from 12 of the 17 factors). Bucci says models in the literature often use only one factor, but this work shows that we need to consider many, and their interactions. This is a big deal.

This is great, says Rishi Raj, an associate professor at the Indian Institute of Technology at Patna, who was not involved in the work. Boiling has such complicated physics. It involves at least two phases of matter, and many factors contributing to a chaotic system. Its been almost impossible, despite at least 50 years of extensive research on this topic, to develop a predictive model, Raj says. It makes a lot of sense to us the new tools of machine learning.

Researchers have debated the mechanisms behind the boiling crisis. Does it result solely from phenomena at the heating surface, or also from distant fluid dynamics? This work suggests surface phenomena are enough to forecast the event.

Predicting proximity to the boiling crisis doesnt only increase safety. It also improves efficiency. By monitoring conditions in real-time, a system could push chips or reactors to their limits without throttling them or building unnecessary cooling hardware. Its like a Ferrari on a track, Bucci says: You want to unleash the power of the engine.

In the meantime, Bucci hopes to integrate his diagnostic system into a feedback loop that can control heat transfer, thus automating future experiments, allowing the system to test hypotheses and collect new data. The idea is really to push the button and come back to the lab once the experiment is finished. Is he worried about losing his job to a machine? Well just spend more time thinking, not doing operations that can be automated, he says. In any case: Its about raising the bar. Its not about losing the job.

Read the original post:
Infrared cameras and artificial intelligence provide insight into boiling - MIT News

Read More..

How to prepare for the AI productivity boom – MIT Sloan News

open share links close share links

The last 15 years have brought what Stanford University professor Erik Brynjolfsson calls the productivity paradox. While theres been continuing advances in technology, such as artificial intelligence, automation, and teleconferencing tools, the U.S. and other countries have seen flagging productivity.

But a productivity boom is coming soon, Brynjolfsson said at the recent EmTech Next conference hosted by MIT Technology Review. He pointed to advances in technology, particularly artificial intelligence programs that are as good as or better than humans at some things. Businesses should now focus on incorporating the technology into work processes and preparing employees, he said, and policymakers should make sure its adoption doesnt contribute to inequality.

Brynjolfsson has been tracking the lag between introduction of artificial intelligence and corresponding productivity gains. United States productivity grew by about 1.3% in the past decade, he said, compared to more than 2.8% in the late 1990s and early 2000s. This productivity slowdown extends to other countries as well, according to research from the Organization for Economic Cooperation and Development. Brynjolfsson predicted a productivity J-curve, in which productivity declines after a technology is introduced and then rises when businesses have been able to integrate technologies into their workflow, a trajectory over time that has a J-shape.

I think were near the bottom of that J-curve right now and were about to see the takeoff, Brynjolfsson said.

Lagging productivity can be explained two main ways, Brynjolfsson said.

Mismeasurement. Productivity is traditionally measured using a countrys gross domestic product, which is based on things that are bought and sold. But many digital goods teleconferencing, smartphone apps, Wikipedia are available for free. Even though people get some benefit from these goods, they dont show up in productivity statistics. The information sectors share of the economy has barely budged since the 1980s, Brynjolfsson noted. I think most of us realize thats just not a real representation of whats going on, he said.

Happiness surveys also fail to capture the complete picture. Brynjolfsson suggested a new metric called GDP-B that would measure the benefit people gain from items. I think its far from perfect, but its a lot more precise than happiness, and I think its a lot more meaningful than GDP, he said.

Implementation and restructuring in businesses. It isnt enough to just add new technology to an organization. Companies need a complete paradigm shift. To get the full benefit, leaders need to rethink business processes, management practices, and employee skills, Brynjolfsson said.

This intangible organizational capital is essential for companies to see benefit from technological advances, but many companies put misplaced focus on technology itself.

The complete reconceptualization of a business process takes a lot. More creativity, effort, and frankly, time, than simply plugging in new technologies into old business processes, he said. We just havent been doing that in most industries.

About a decade ago, machine learning programs had about 70% accuracy, Brynjolfsson said. They have improved rapidly, to the point that they are now better than humans at identifying some things. This makes it more likely that organizations will move to integrate this technology into their business practices as entrepreneurs and managers gravitate toward these often cheaper and more efficient approaches.

We dont need any additional advances in technology to be able to have enormous effects on productivity and wages, he said.What we do need is some significant changes in business processes. We need to rethink the way work gets done.

There are signs more businesses are taking advantage of artificial intelligence programs. The 2021 AI Index report, which Brynjolfsson co-authored, found increases in not just the quality of artificial intelligence, but also business investment in the technology. The biggest increase was in the field of drug discovery and other biological uses of AI, with a 4.5% increase in investment in drug discovery in the last year.

Powerful technology is available, and every organization has an opportunity to benefit from it, he said. Successful firms will be prepared with the skills needed in the future, and leaders should focus on reskilling their workforce.

Replacing labor with capital and human work with technology brings concerns about decreased wages and increased inequality. Brynjolfssons research has documented how machine learning affects different skills and occupations, and found that there isnt one occupation where machine learning could do all the different tasks. While machine learning will likely reorganize work, it wont mean the end of work or entire occupations, he said.

But the effects will likely be uneven. The economic pie could get bigger, but that doesnt mean everyones going to benefit, Brynjolfsson said. Theres been some evidence of this happening, he said, with his research also indicating machine learning is more likely to affect low-wage occupations.

Inequality isnt inevitable, though. Brynjolfsson argued that to a large extent, it is the result of tax and education policies. He suggested three measures that companies, institutions, and policymakers can take to make sure all workers benefit from the productivity boom:

Reskilling the workforce. Taking advantage of AI and other technologies require different sets of skills. Im not just talking about more machine learning experts. Im talking about people who do more creative work, Brynjolfsson said. And while machines are able to do rote, repetitive work, companies will need people who are skilled at interpersonal, emotional connections.

Adjusting tax policy. Capital is taxed at a lower rate than labor, which might push companies to favor technology over workers. Brynjolfsson suggested leveling the playing field, or introducing measures such as earned income tax credits that help subsidize work.

Focusing on technologies that augment workers instead of replace them. Brynjolfsson said he is working on research that shows how technologists are focused on creating programs that replicate human skills. While that may be a fun goal, it actually isnt a particularly good one in terms of helping reduce inequality. It tends to drive down wages, he said. Id rather have them focused on augmenting human labor.

Here is the original post:
How to prepare for the AI productivity boom - MIT Sloan News

Read More..

COVID: Artificial intelligence in the pandemic – DW (English)

If artificial intelligence is the future, then the future is now. This pandemic has shown us just how fast artificial intelligence, or AI, works and what it can do in so many different ways.

Right from the start, AI has helped us learn about SARS-CoV-2, the virus that causes COVID-19 infections.

It's helped scientists analyse the virus' genetic information its DNA at speed. DNA is the stuff that makes the virus, indeed any living thing, what it is. And if you want to defend yourself, you had better know your enemy.

AI has also helped scientists understand how fast the virus mutates and helped them develop and test vaccines.

We won't be able to get into all of it this is just an overview. But let's start by recapping the basics about AI.

An AI is a set of instructions that tells a computer what to do, from recognizing faces in the photo albums on our phones to sifting through huge dumps of data for that proverbial needle in a haystack.

People often call them algorithms. It sounds fancy but an algorithm is nothing more thana static list of rules that tells a computer: "If this, then that."

A machine learning (ML) algorithm, meanwhile, is the kind of AI that many of us like to fear. It's an AI that can learn from the things it reads and analyzes and teach itself to do new things. And wehumansoften feel like we can't control or even know what ML algorithms learn. But actually, we can because we write the original code. Soyou can afford to relax. A bit.

In summary, AIs and MLs are programs that let us process lots and lots of information, a lot of it "raw" data, very fast. They are not all evil monsters out to kill us or steal our jobs not necessarily, anyway.

With COVID-19, AI and ML may have helped save a few lives. They have been used in diagnostic tools that read vast numbers of chest X-raysfaster than any radiologist. That's helped doctors identify and monitor COVID patients.

In Nigeria, the technology has been used at a very basic but practical level to help people assess their of risk of getting infected. People answer a series of questions online and depending on their answers, are offered remote medical advice or redirected to a hospital.

The makers, a company called Wellvis, say it has reduced the number of people calling disease control hotlines unnecessarily.

One of the most important things we've had to handle is finding out who is infected fast. And in South Korea, artificial intelligence gave doctors ahead start.

Way back when the rest of the world was still wondering whether it was time to go into the first lockdown, a company in Seoul used AI to develop a COVID-19 test in mere weeks. It would have taken them months without AI.

It was "unheard of," said Youngsahng "Jerry" Suh, head of data science and AI development at the company, Seegene, in an interview with DW.

Seegene's scientists ordered raw materials for the kits on January 24 and by February 5, the first version of the test was ready.

It was only the third time the company had used its supercomputer and Big Data analysis to design a test.

But they must have done something right because by mid-March 2020, international reports suggested that South Korea had tested 230,000 people.

And, at least for a while, the country was able to keep the number of new infections per day relatively flat.

"And we're constantly updating that as new variants and mutations come to light. So, that allows our machine learning algorithm to detect those new variants as well," says Suh.

One of the other major issues we've had to handle is tracking how the disease especially new variants and their mutations spread through a community and from country to country.

In South Africa, researchers used an AI-based algorithm to predictfuture daily confirmed cases of COVID-19.

It was based on historical data from South Africa's past infection history and other information, such as the way people move from one community to another.

In May, they say they showed the country had a low risk of a third wave of the pandemic.

"People thought the beta variant was going to spread around the continent and overwhelm our health systems, but with AI we were able to control that," says Jude Kong, who leadsthe Africa-Canada Artificial Intelligence and Data Innovation Consortium.

The project is a collaboration between Wits University and the Provincial Government of Gauteng in South Africa and York University in Canada, where Kong, who comes from Cameroon, is an assistant professor.

Kong says "data is very sparse in Africa" and one of the problems is getting over the stigma attached to any kind of illness, whether it's COVID, HIV, Ebola or malaria.

But AI has helped them "reveal hidden realities" specific to each area, and that's informed local health policies, he says.

They have deployed their AI modelling in Botswana, Cameroon, Eswatini, Mozambique, Namibia, Nigeria, Rwanda, South Africa, and Zimbabwe.

"A lot of information is one-dimensional," Kong says. "You know the number of people entering a hospital and those that get out. But hidden below that is their age, comorbidities, and the community where they live. We reveal that with AI to determine how vulnerable they are and inform policy makers."

Other types of AI, similar to facial recognition algorithms, can be used to detect infected people, or those with elevated temperatures, in crowds. And AI-driven robots can clean hospitals and other public spaces.

But, beyond that, there are experts who say AI's potential has been overstated.

They include Neil Lawrence, a professor of machine learning at the University of Cambridge who was quoted in April 2020, calling out AI as "hyped."

It was not surprising, he said, that in a pandemic, researchers fell back on tried and tested techniques, like simple mathematical modelling. But one day, he said, AI might be useful.

That was only 15 months ago. And look how far we've come.

That's how to do it: If humans have COVID-19, dogs had better cuddle with their stuffed animals. Researchers from Utrecht in the Netherlands took nasal swabs and blood samples from 48 cats and 54 dogs whose owners had contracted COVID-19 in the last 200 days. Lo and behold, they found the virus in 17.4% of cases. Of the animals, 4.2% also showed symptoms.

About a quarter of the animals that had been infected were also sick. Although the course of the illness was mild in most of the animals, three were considered to be severe. Nevertheless, medical experts are not very concerned. They say pets do not play an important role in the pandemic. The biggest risk is human-to-human transmission.

The fact that cats can become infected with coronaviruses has been known since March 2020. At that time, the Veterinary Research Institute in Harbin, China, had shown for the first time that the novel coronavirus can replicate in cats. The house tigers can also pass on the virus to other felines, but not very easily, said veterinarian Hualan Chen at the time.

But cat owners shouldn't panic. Felines quickly form antibodies to the virus, so they aren't contagious for very long. Anyone who is acutely ill with COVID-19 should temporarily restrict outdoor access for domestic cats. Healthy people should wash their hands thoroughly after petting strange animals.

Should this pet pig keep a safe distance from the dog when walking in Rome? That question may now also have to be reassessed. Pigs hardly come into question as carriers of the coronavirus, the Harbin veterinarians argued in 2020. But at that time they had also cleared dogs of suspicion. Does that still apply?

Nadia, a four-year-old Malaysian tiger, was one of the first big cats to be detected with the virus in 2020 at a New York zoo. "It is, to our knowledge, the first time a wild animal has contracted COVID-19 from a human," the zoo's chief veterinarian told National Geographic magazine.

It is thought that the virus originated in the wild. So far, bats are considered the most likely first carriers of SARS-CoV-2. However, veterinarians assume there must have been another species as an intermediate host between them and humans in Wuhan, China, in December 2019. Only which species this could be is unclear.

This racoon dog is a known carrier of the SARS viruses. German virologist Christian Drosten spoke about the species being a potential virus carrier. "Racoon dogs are trapped on a large scale in China or bred on farms for their fur," he said. For Drosten, the racoon dog is clearly the prime suspect.

Pangolins are also under suspicion for transmitting the virus. Researchers from Hong Kong, China and Australia have detected a virus in a Malaysian Pangolin that shows stunning similarities to SARS-CoV-2.

Hualan Chen also experimented with ferrets. The result: SARS-CoV-2 can multiply in the scratchy martens in the same way as in cats. Transmission between animals occurs as droplet infections. At the end of 2020, tens of thousands of martens had to be killed in various fur farms worldwide because the animals had become infected with SARS-CoV-2.

Experts have given the all-clear for people who handle poultry, such as this trader in Wuhan, China, where scientists believe the first case of the virus emerged in 2019. Humans have nothing to worry about, as chickens are practically immune to the SARS-CoV-2 virus, as are ducks and other bird species.

Author: Fabian Schmidt

Continue reading here:
COVID: Artificial intelligence in the pandemic - DW (English)

Read More..

The smart role of Artificial Intelligence in todays world – BL on Campus

Artificial Intelligence (AI) has been redefining society in ways we have never anticipated. Technology is clinging to us in every walk of our lives, right from unlocking our smartphones to our day-to-day activities, online shopping, intelligent car dashboards, autonomous robots and so on. Though the concept of AI was first talked about in the early 1950s, forming a basis for many computer learning and complex decision-making processes, it is only of late, where processing huge amounts of data is required, that this field of technology is picking up pace.

What is in the AI basket?

AI is not a technology, rather it is a science or field of study. It is a constellation that encompasses a lot of statistical computation methods, pre and post analyses techniques for handling structured and unstructured data. It is an interesting endeavour of replicating and stimulating human intelligence through machine and deep learning platforms, natural language generation, virtual agents, text-voice-image recognition, AI optimised hardware, robotic process automation, cognitive search system and so on. It has a goal of utilising all the technologies to make intelligent machines.

Growth of AI in India

AI is the tool of innovation being experimented with, in almost all Indian domains, including healthcare, education, agriculture, finance, automobiles, energy, retail, manufacturing, scientific research with autonomous discoveries in place. In India, companies like Walmart, Google, Microsoft, Amazon, Samsung are into AI-based research and product offerings. Still, our country has a lot of potential to expand its research in this cutting-edge technology. Most of our educational, government and private institutes cradle and motivate AI researchers, innovations and start-ups.

The Government is pushing the private sector and offers many opportunities through DST, Niti Aayog, IndiaAI and many more, to create innovative technological solutions and fund AI-based start-ups. The start-ups are focussed in the cities like Bengaluru, Hyderabad, Ahmedabad, Mumbai, Delhi for AI-based businesses.

Why AI matters in todays scenario

AI, which emerged from the research world as a proof-of-concept has been strategically scaling up due to the pace of digitisation. AI is favoured for its large data processing, end-to-end efficiency of decoding complex processes, improved accuracy and help in decision-making, intelligent offerings, smart services - content, task automation and so on. We can see its overwhelming development in healthcare, pharmaceutical, scientific research, and e-commerce.

The interactive applications of Google, DeepMinds Alpha Fold, BenevolentAI, chatbots such as Clara and Zini; Aryoga Setu, Co-Win, Amazon, Zomato, Swiggy are among the few proving to be our pandemic tech saviours.

Impact of AI in business

Business over the years has evolved from local corner shops to the booming online shopping platforms. These modernised techniques not only make individual lives easier, but also streamline business processes for improving consumer experience, sales forecasting and automated decision making to meet business goals. Businesses work well when humans, machines and technologies integrate for each others benefit. Todays business world is solely dependent on AI, Cloud, Big Data technologies of which e-commerce and m-commerce are the mainstream, having a great business impact globally. In synch with global developments in innovation and automation, India too has brought about a digital transformation over the last two decades. Now, technological developments have gained pace more than what has been predicted; the pandemic played a great role in its quick transformation and adoption.

How to look for jobs in AI?

Today, Artificial Intelligence is a lucrative domain, promising job growth in a competitive IT industry. Four out of five C-suite executives believe that they need to speed up data processing and automation, if they have to survive in their business. So, recruiters look for advanced technical skills, extensive practical experience. AI skills secure the top place among the fastest growing job profiles over the recent years. The prominent job roles include big data engineer, business intelligence developer, data scientist, data analyst, cyber analyst and expert, AI-Deep learning-machine learning engineer, computer vision specialist along with equivalent research jobs.

How can one find a good job in AI? The answer is, there are several avenues and opportunities to be had by connecting with experts via LinkedIn, technical blogs, career fairs and company career sites. The tech talks given by companies in university, conclaves hosting academics-government-industry groups will help you understand the actual employment needs and goals. Always aim to seek opportunities at government and industry-funded research labs during the early years of your higher education. This will help you to nurture your skillset to the best. Work for open-source and stack overflow contributions which will add value to your technical profile. Technical competitions like hackathons/ideathons/makeathons will upskill your innovative ideas along with the required life skills.

Globally, today we are in a challenging situation. All, irrespective of the sectors, are working on the revamp strategy to balance the economy post Covid-19. AI will endeavour to revive the profitability and development of industry . New and advanced opportunities are expected to open up.

AI is and will be driving a promising future in the new normal. It will be the main driver for emerging and new technologies. So, take an interdisciplinary approach to hone your skills in an ever-evolving field. Think big, start small, act fast.

(The writer is Professor & Chairperson, School of Computing, SRM Institute of Science and Technology.)

See original here:
The smart role of Artificial Intelligence in todays world - BL on Campus

Read More..