Dr Sunil Kumar Vuppala, an IIT Roorkee alumnus, has won the Zinnov Award 2020 for his contribution to Artificial Intelligence (AI) and Data Analytics.

Dr Sunil Kumar Vuppala, an IIT Roorkee alumnus, has won the Zinnov Award 2020 for his contribution to the field of Artificial Intelligence (AI) and Data Analytics. The objective of the award is to recognize the contribution of individuals as well as organizations that have enabled business continuity driven innovation along with diversity.

Dr Vuppala, from the 2004 batch of IIT Roorkees Department of Electronics and Communication Engineering, is currently serving as Director - Data Science, Ericsson, and Co-chair, Industry Engagement, IEEE Bangalore Section.

He has been conferred the award in the Technical Role Model-Emerging Technology - AI and Big data analytics award category in a virtual ceremony on July 31, 2020.

We extend our heartiest congratulations to Dr Vuppala for winning this prestigious award. It is a proud moment for IIT Roorkee. His achievement will inspire other alumni as well as current students, said Prof Ajit K Chaturvedi, Director, IIT Roorkee.

I am elated to receive the award. I would like to thank my family, my alma mater- IIT Roorkee, and well-wishers for their support and guidance, said Dr Vuppala.

The tech-driven education at IIT Roorkee laid the foundation for my strong fundamentals in the emerging technologies domain. Equally relevant is the role of the faculty at IIT Roorkee, who has been a constant pillar of support, he added.

Other notable recipients of the 2020 awards included Manish Bhide Chief Architect, IBM Watson OpenScale, and Shibi Panikkar Distinguished Engineer from Dell Technologies.

This was the 11th edition of the annual awards that witnessed participation from over 600 plus companies in 10 plus countries.

In the past 11 years, Zinnov Confluence Series has honoured numerous individuals as well as entities for their contribution to global technology and for making a difference in the global ecosystem.

A technology thought leadership summit, Zinnov Awards, has become synonymous with change in the Global R&D and Product Development space.

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IIT Roorkee Alumnus Wins Zinnov Award For Contribution To Artificial Intelligence - NDTV

The Tory Burch Foundation Summit in early March was a gathering of some of the most prominent executives and entrepreneurs in the world.

Bank of America COO Thomas Montag former AOL CEO Steve Case, and Dina Powell McCormick, partner and member of the Management Committee at Goldman Sachs, were a few of the execs who spoke about how they sought to make their companies more inclusive.

A prominent theme throughout the conference was gender parity in the workplace.

The word ambition takes on a completely different meaning when applied to a woman than when applied to a man, Burch told Business Insider. Women are criticised for exhibiting the exact same quality men are praised for. This has to change. We do that by shining a light on unconscious gender bias, which was the focus of our Summit.

Yasmin Green, director of research and development at Jigsaw, a unit of Google parent company Alphabet, spoke about one particularly complex hurdle in modern society: the difficulty of programming artificial intelligence without bias.

The problem with training AI on humans, Green said, is that humans are biased, and when the data that feeds AI is biased, then the AI becomes biased itself.

Green detailed an experiment that demonstrated this unconscious bias in AI. She and her team created the same fake professional profile for a woman and a man and browsed online job sites as each of these imaginary people. In the end, they found that men were five times as likely to see ads for higher-paying jobs than women.

This, she said, was because women believe they must fulfil 100% of the requirements before they apply to a job, whereas men believe they only need to meet at least 60% of the requirements before they apply to the job.

So at the same skill level, we [women] are clicking on jobs that are less senior and less well paid, Green said. But if we click that way, then the internet is going to learn and thats what were going to see.

Green cited another example, in which she and her team had trained an AI model to pick up on hate speech on social media. After a few trials, their AI model began to flag the sentence, I am a proud gay man, as a hate sentence.

Green said this was because they trained the AI model by using millions of example sentences that humans wrote on the internet, and most sentences and comments that contained the word gay were negative 80% of them, in fact.

Therefore, the AI model Greens team experimented with took this data and learned to associate the term gay with something negative and hateful.

I ask myself how can I raise my daughters to make good decisions in life, [and] to be more compassionate and less prejudiced than the world around them, Green said at the conference. The question for us are we content with algorithms that reflect back to us the way the world works?

To help prevent situations like this and lessen the bias in AI, Green said social justice activism needs to be expanded to include algorithm. She also noted the importance of having diverse representation in AI programming.

Its not enough just to automate human behaviour, she said. We need to make sure that whats reflected back to us in algorithms is something thats better than we are.

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Why artificial intelligence models are often biased, according to the Google exec who heads Alphabet's internal tech incubator Jigsaw - Business...

The dream of creating a machine that emulates human behavior has been an obsession throughout human history. Artificial Intelligence (AI) has been in our minds for many years, since Adam's creation: "God creates him from a moldable material, programs him, and gives him the first instructions (Snchez-Martn et al. 2007)." Even in Greek mythology with Ovid's account of Pygmalion sculpting a figure of a beautiful woman who is given life for Pygmalion to love her. In Hebrew mythology, the Golem was created with clay and animated to save the inhabitants of a Jewish city. In Norse mythology, the giant Mkkurklfi or Mistcalf was created from clay to support the troll Hrungnir in his fight against Thor. In each epoch, the examples continue.

Artificial Intelligence (AI), in its most natural sense, is about how to simulate the capabilities of human brain intelligence, so thinking about AI is also thinking about what makes it possible for us to interact and learn. Its applications can contribute significantly to education (Ocaa-Fernndez, Valenzuela-Fernndez, and Garro-Aburto, 2019).

The COVID-19 pandemic has provoked substantial educational changes, among them the migration to virtual learning ecosystems. Teachers must confront the task of attending a wide variety of needs to ensure that students' education continues. Artificial intelligence can be ideal pedagogical support to facilitate attention to our students at any time. Imagine how it can help you respond to each student's questions in real-time while being confident that the student is being oriented correctly. Also, you can take advantage of that time to study some topics of interest, deepen the development of your class, conduct research, build teaching sequences, and perform Mindfulness activities to potentiate your creativity and innovation, to cite some ideas. Wouldn't this be fabulous?

The main objective is to provide our colleagues with the opportunity to build an intelligent pedagogical assistant through a chatbot, which contributes to solving a large part of the students' concerns. The structuring of the responses was designed with the flipped learning approach to provide feedback on class concerns.

What are the real possibilities of applying AI in education? Could AI be a key component in a new educational model? Can you imagine having a colleague who helps us answer hundreds of common questions from our students around the clock or updating anyone who could not connect to the class on time? You probably think that this means having an assistant advisor or a teacher's assistant. Well, this is not so far from our reach.

The journey of artificial intelligence began with Alan Turing in 1936 with the publication of his famous article, "On Computable Numbers, with an Application to The Entscheidungsproblem." The paper established the bases of theoretical computing and the origin of the concept "Turing Machine," which formalized the algorithm concept that would become the precursor process of digital computers. In 1956, at the mythical Dartmouth conference, John McCarthy, Marvin Minsky, and Claude Shannon coined the term "Artificial Intelligence." Even though there was much positive speculation about this technology, AI indeed jumped on the world stage in1997 when the IBM computer, Deep Blue, beat world-chess-champion Gari Kasparov. A profound reflection on its potential began in different fields, like science fiction, computer science, mathematics, social sciences, and even humanities.

A little later, the computer Watson, also from IBM, would win a duel against the human brain in "Jeopardy," the famous quiz show of questions and answers on the American television network, ABC. Isaac Asimov wrote the eminent three laws of robotics that brought us closer to thinking about the ethical problems that the development of artificial intelligence brings us so that we might avoid the revelations of science fiction like that of Hal 9000 in 2001: A Space Odyssey.

In recent years we have seen significant progress. In March 2019, the High-Level Expert Group on AI (AI HLEG), a steering group for the European AI Alliance, drew up a draft of AI ethical guidelines that help us understand the relevance of this topic being attended not only in the area of technology but also in the social sciences and humanities.

Artificial Intelligence can be categorized into three levels that allow us to locate ourselves as we navigate the continuum of incremental innovation, starting with incorporating this technology into our daily lives, especially in education.

Level 1: Revolutionary. Big technology companies such as Google, Microsoft, and Hanson Robotics seek to improve living conditions in everyday life and affect our home, cars, food, and health. An example of this is Google's supercomputer and Sophia, the humanoid robot.

Level 2: Expansion. At this level, AI is used to boost production to a larger scale in areas such as communication, the everyday market, and risk analysis on the stock exchange. An example of this is Amazon's machine learning systems.

Level 3: Communication. At this level appear the fundamental processes of interaction with free software that seeks to respond to users' needs either by programming or emulating mechanical learning of the likely responses that are helpful. Examples include natural language comprehension platforms such as Dialogflow, Botmake.io, Cliengo, Snathbot.me, and Manychat.

In education, level 3 tools are alternatives that respond to teaching needs. In particular, a tool we can call chatbot, platforms that understand natural language, and allow the programming of automatic responses emulate human conversations.

At the University of the East in Mexico, we use the Dialogflow tool for processes oriented to our students' accompaniment with significant advantages that I share below.

The main objective is to encourage our colleagues to take advantage of the opportunity to build a pedagogical assistant that helps to resolve many of the students' concerns. The structuring of the responses was explicitly geared to the flipped learning approach, which facilitates feedback to the students about their interests. This approach benefits the students by readily available answers and referring them to multimedia reference sources that extend and improve their experience.

We decided to load the application on Moodle, the institutional platform for academic reinforcement, to ensure that the pedagogical assistants were customized to the classes' needs. The desired results of this implementation were to equip our teachers with more competitive and functional tools to support our students in accompanied activities within a context of constant communication. The main challenge for those participating in this project is to ensure that the responses are much more dynamic and lead to more meaningful contributions.

The academic work with this type of chat allows us, in addition to maintaining a relationship of communication with our students, to link the conversation to other tools that help our students confront challenges through learning capsules that deepen or engage them in contexts of professional development.

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How to Apply Artificial Intelligence in Education? - Observatory of Educational Innovation

Artificial Intelligence in Drug Discovery Market Expected to Witness High Growth over the Forecast Period 2020 - 2026Published: 49 minutes ago Author: Ashwin NaphadeCategory: #news

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Artificial Intelligence in Drug Discovery Market Expected to Witness High Growth over the Forecast Period 2020 - 2026 - AlgosOnline

From the smallest local business to the largest global players, I believe every organization must embrace the AI revolution, and identify how AI (artificial intelligence) will make the biggest difference to their business.

3 Important Ways Artificial Intelligence Will Transform Your Business And Turbocharge Success

But before you can develop a robust AI strategy in which you work out how best to use AI to drive business success you first need to understand whats possible with AI. To put it another way, how are other companies using AI to drive success?

Broadly speaking, organizations are using AI in three main ways:

Creating more intelligent products

Offering a more intelligent service

Improving internal business processes

Lets briefly look at each area in turn.

Creating more intelligent products

Thanks to the Internet of Things, a whole host of everyday products are getting smarter. What started with smartphones has now grown to include smart TVs, smartwatches, smart speakers, and smart home thermostats plus a range of more eyebrow-raising "smart" products such as smart nappies, smart yoga mats, smart office chairs, and smart toilets.

Generally, these smart products are designed to make customers lives easier and remove those annoying bugbears from everyday life. For example, you can now get digital insoles that slip into your running shoes and gather data (using pressure sensors) about your running style. An accompanying app will give you real-time analysis of your running performance and technique, thereby helping you avoid injuries and become a better runner.

Offering a more intelligent service

Instead of the traditional approach of selling a product or service as a one-off transaction, more and more businesses are transitioning to a servitization model, in which the product or service is delivered as an ongoing subscription. Netflix is a prime example of this model in action. For a less obvious example, how about the Dollar Shave Club, which will deliver razor blades and grooming products to your door on a regular basis. Or Stich Fix, a personalized styling service that delivers clothes to your door based on your personal style, size, and budget.

Intelligent services like this are reliant on data and AI. Businesses like Netflix have access to a wealth of valuable customer data data that helps the company provide a more thoughtful service, based on what it knows the customer really wants (whether its movies, clothes, grooming products or whatever).

Improving internal business processes

In theory, AI could be worked into pretty much any aspect of a business: manufacturing, HR, marketing, sales, supply chain and logistics, customer services, quality control, IT, finance and more.

From automated machinery and vehicles to customer service chatbots and algorithms that detect customer fraud, AI solutions and technologies are being incorporated into all sorts of business functions in order to maximize efficiency, save money and improve business performance.

So, which area should you focus on products, services, or business processes?

Every business is different, and how you decide to use AI may differ wildly from even your closest competitor. For AI to truly add value in your business, it must be aligned with your companys key strategic goals which means you need to be clear on what it is you're trying to achieve before you can identify how AI can help you get there.

That said, its well worth considering all three areas: products, services and business processes. Sure, one of the areas is likely to be more of a priority than the others, and that priority will depend on your companys strategic goals. But you shouldnt ignore the potential of the other AI uses.

For example, a product-based business might be tempted to skip over the potential for intelligent services, while a service-based company could easily think smart products arent relevant to its business model. Both might think AI-driven business processes are beyond their capabilities at this point in time.

But the most successful, most talked-about companies on the planet are those that deploy AI across all three areas. Take Apple as an example. Apple built its reputation on making and selling iconic products like the iPad. Yet, nowadays, Apple services (including Apple Music and Apple TV) generate more revenue than iPad sales. The company has transitioned from purely a product company to a service provider, with its iconic products supporting intelligent services. And you can be certain that Apple uses AI and data to enhance its internal processes.

In this way, AI can throw up surprising additions and improvements to your business model or even lead you to an entirely new business model that you never previously considered. It can lead you from products to services, or vice versa. And it can throw up exciting opportunities to enhance the way you operate.

Thats why I recommend looking at products, services, and business processes when working out your AI priorities. You may ultimately decide that optimizing your internal processes (for example, automating your manufacturing) is several years away, and thats fine. The important thing is to consider all the AI opportunities, so that you can properly prioritize what you want to achieve and develop an AI strategy that works for your business.

AI is going to impact businesses of all shapes and sizes, across all industries. Discover how to prepare your organization for an AI-driven world in my new book, The Intelligence Revolution: Transforming Your Business With AI.

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3 Important Ways Artificial Intelligence Will Transform Your Business And Turbocharge Success - Forbes

Press Trust of IndiaAug 03, 2020 11:55:43 IST

The India Meteorological Department (IMD) is planning to use artificial intelligence in weather forecasting, especially for issuing nowcasts, which can help improve 3-6 hours prediction of extreme weather events, its Director General Mrutunjay Mohapatra said on Sunday.

He said the use of artificial intelligence and machine learning is not as prevalent as it is in other fields and it is relatively new in the area of weather forecasting.

The IMD has invited research groups who can study how artificial intelligence (AI) be used for improving weather forecasting and the Ministry of Earth Sciences is evaluating their proposals, Mohapatra said.

He said the IMD is also planning to do collaborative studies on this with other institutions.

Also read:IMD releases weather apps Mausam, Meghdoot for public, farmers to track forecasts, warnings, imagery in real-time

IMD could soon be using AI alongside its current weather forecasting technology. Image Credit StormGeo

The IMD uses different tools like radars, satellite imagery, to issue nowcasts, which gives information on extreme weather events occurring in the next 3-6 hours.

The IMD issues forecasts for extreme weather events like thunderstorms, dust storms. Unlike cyclones, predictions of thunderstorms, which also bring lightning, squall and heavy rains, are more difficult as the extreme weather events develop and dissipate in a very short period of time.

Last month, over 160 people died due to lightning alone in Uttar Pradesh and Bihar.

The IMD wants to better the nowcast predictions through AI and machine learning.

"Artificial intelligence helps in understanding past weather models and this can make decision-making faster," Mohapatra said.

The National Oceanic and Atmospheric Administration (NOAA) of the US announced new strategies this year to expand the agency's application of four emerging science and technology focus areas NOAA Unmanned Systems, artificial intelligence, Omics, and the cloud -- to guide transformative advancements in the quality and timeliness of NOAA science, products and services.

Omics is a suite of advanced methods used to analyse material such as DNA, RNA, or proteins.

With regards to AI, it said the overarching goal of the NOAA Artificial Intelligence (AI) Strategy is to utilise AI to advance NOAA's requirements-driven mission priorities.

The NOAA said through this, it seeks to reduce the cost of data processing, and provide higher quality and more timely scientific products and services for societal benefits.

Find latest and upcoming tech gadgets online on Tech2 Gadgets. Get technology news, gadgets reviews & ratings. Popular gadgets including laptop, tablet and mobile specifications, features, prices, comparison.

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IMD to explore artificial intelligence to improve forecasting, predict extreme weather events - Firstpost

Is it just the LifeStyler or are others noticing just how many brands are claiming to have artificial intelligence built into their products?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

AI is not the ability to turn a kettle off once the water has boiled but would be AI if the kettle determined by itself that at 11 am on days below 25 degrees you had a cup of coffee and worked out that you were indeed at home it would boil the kettle ready for you at 11 am only on cooler days.

Thus AI is the ability to make decisions with lots of variable pieces of information. What the LifeStyler is annoyed about is the ability of marketers to throw the term around adding it to the description of their product inferring it is smarter than it is. AI is one of those things like the cloud that most people dont understand but are too embarrassed to admit they dont. Further, they fall into the trap of it must be better if the word is used.

To take this a step further technically, Google and Alexa are examples of machine learning, not AI.

My challenge to the readers is to call out products that are truly AI versus products that are just pretending to be AI. Cheers!

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Not so Artificial Intelligence When is AI really AI? - EFTM

Amazon has a project they call Rekognition. Its an AI-based facial recognition software thats marketed to police agencies for use in investigations. Its essentially supposed to cross analyze images and direct law enforcement officers to possible suspects. The problem is that its not very accurate.

In a study by the Massachusetts chapter of the ACLU, dozens of Boston-area athletes pictures were run through the system. At least 27 of these athletes or roughly one-in-six were falsely matched with mugshots. This included three-time Super Bowl champion Duron Harmon of the New England Patriots.

Can you say, not a good look?

Users Find Flaws in Apples Face ID

Apple is always coming up with cutting edge technology. Theyve set the standards in the smartphone and mobile device industry for years. For the most part, they get things right. But sometimes they can be a bit too brash in their marketing. In other words, they like to flex their muscles. As you might expect, this invites haters, trolls, and skeptics to challenge their claims.

One recent example occurred with the release of the iPhone X. Leading up to the launch, Apple had invested a lot of time and marketing dollars into their front-facing facial recognition system that replaced the fingerprint reader as the primary method of accessing the phone. The claim was that the AI component was so smart readers could wear glasses, makeup, etc. without compromising functionality. And thats essentially true. The problem is that Apple also clearly stated the Face ID technology cant be spoofed by masks or other techniques.

One Vietnam-based security firm took this as a challenge. And with just $200, they made a mask out of stone powder, glued on some printed 2D eyes, and unlocked a phone. This is just a reminder that bold claims can sometimes come back to bite!

Robot Dog Meets Fatal Ending

Who doesnt love the idea of a robot puppy? You get a cute little machine without the barking, walking, pooping, eating, or expensive vet bills. But if youre looking for a life partner, you might not want this robodog.

In 2019, a Boston Robotics robodog named Spot met a dramatic and untimely onstage death while he was being demoed by the company CEO at a conference in Las Vegas. Tasked with walking, he slowly started to stumble and eventually collapsed to the floor as the audience uncomfortably gasped and chuckled.

Watson Is Not a Doctor

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Examples of Failure in Artificial Intelligence - ReadWrite

What are the best robotics and artificial intelligence stocks to buy today? In this time of uncertainty characterized by volatile market movements, economic contraction, and spiraling unemployment, finding stocks to put your money into seems like an arduous task. Some investors might think that the stock market is acting irrationally and puzzled by the quick recovery of stock prices sin the end of March. The market's movements isn't far away from economic realities. Economic reality is that long-term real interest rates are negative, the Federal Reserve is flooding the market with cheap credit, and the current economic slowdown is temporary.

This is the perfect environment to buy technology stocks which aren't negatively affected by the coronavirus induced lockdowns and economic slowdown. In this article we are going to take a look at the top 5 robotics and artificial intelligence stocks to buy. We are on the cusp of a technological revolution that will fundamentally change how we live our lives. Recent advancements in machine learning and artificial intelligence will open the door to robots, driving cars, and many other inventions that we can't even imagine today. So, we decided to take a look at the best robotics and AI stocks to buy in order to generate high returns as the companies bring new products in to the marketplace.

robotics and AI stocks

In order to compile this list of best robotics and AI stocks to buy we started with top 15 stocks in the Global X Robotics & Artificial Intelligence ETF (BOTZ). According to its website this ETF "seeks to invest in companies that potentially stand to benefit from increased adoption and utilization of robotics and artificial intelligence (AI), including those involved with industrial robotics and automation, non-industrial robots, and autonomous vehicles".

Savvy investors have used hedge funds as a litmus test to gauge the profitability of stocks and to know the trajectory of market sentiment. Research carried out by Insider Monkey has shown that a select group of hedge fund holdings have consistently outperformed the S&P 500 ETFs by more than 56 percentage points since March 2017 (see the details here). As such, hedge fund sentiments are undoubtedly a useful indicator that experienced investors should pay attention to.

Based on hedge funds sentiment, we present 5 most popular robotics and AI stocks among the 800+ hedge funds tracked by Insider Monkey.

5. John Bean Technologies Corporation (NYSE:JBT)

John Bean Technologies Corporation (NYSE:JBT) provides technology solutions to the food and beverage industry, including equipment and services to air transportation industries. The company has a market capitalization of $2.995bn. This stock has underperformed by -18.4%. In 2020, Q1 John Bean Technologies Corporation (NYSE:JBT) released quarterly earnings of $1.09 per share. This compares to earnings of $1.42 per share a year ago

The company is poised to gain from focus on developing innovative products and services and expanding the aftermarket business on the effects of the pandemic are over. The management also aims to continue its Elevate Plan aiming to drive persistent growth and margin expansion and strategic acquisition programs. Growing demand for protein, beverages and ready-to-eat meals are likely to act as key catalysts in the long haul.

John Bean Technologies Corporation (NYSE:JBT) is in the portfolio of 12 hedge funds. Royce Associates has the biggest position in JBT in our database. Adage Capital and Citadel are also invested in this stock but they have been trimming their holdings more recently.

4. Brooks Automation, Inc. (NASDAQ:BRKS)

Story continues

Brooks Automation, Inc. (NASDAQ:BRKS) provides automation and cryogenic solutions worldwide. The company operates in two segments, Brooks Semiconductor Solutions Group and Brooks Life Science Systems. The company has a market capitalization of $3.49bn. This year, the company's share price has increased by 10.84%. In 2020,

Brooks Automation is in the portfolio of 18 hedge funds. Billionaire Ken Fisher, Chuck Royce, and Paul Marshall And Ian Wace are among the top hedge fund backers of BRKS.

3. iRobot Corporation (NASDAQ:IRBT)

iRobot Corporation (NASDAQ:IRBT) Robot Corporation designs, builds and sells robots for the consumer market in the United States, Europe, the Middle East, Africa, and internationally. The company has a market capitalization of $2.052bn, while its share price has increased by 51.3% this year. iRobot Corporation (NASDAQ:IRBT) maintained its earnings streak in the second quarter of 2020, reporting earnings of $1.06 per share. Healthy sales growth and improved margins aided the year-over-year rise of 120.8%, as revenues of $279.9 million were reported for the quarter.

It is no surprise that the company is in the portfolio of 19 hedge funds. Quant hedge fund Two Sigma has the biggest equity position in IRBT in our database.

2. Intuitive Surgical, Inc. (NASDAQ:ISRG)

Intuitive Surgical, Inc. (NASDAQ:ISRG), together with its subsidiaries, designs, manufactures and markets da Vinci surgical systems and related instruments in the United States and internationally. The company has a market capitalization of $80.443B. This yeas alone, shares of Intuitive Surgical, Inc. (NASDAQ:ISRG) have increased by 15%.

Though the company reported adjusted earnings per share (EPS) of $1.11, for 2020 Q2, earnings plunged 65.8% year over year. The companys reported revenues also declined by 22.5% totalling $852.1 million. Adjusted operating income, which totaled $193.3.3 million, was down by 57.5% year over year.

Fifty hedge funds had bullish positions in Intuitive Surgical, Inc. (NASDAQ:ISRG) at the end of the first quarter. The largest stake in Intuitive Surgical, Inc. (NASDAQ: ISRG) is held by Fisher Asset Management, which reported holding $350.1 million worth of stock at the end of September. It was followed by GQG Partners with a $137.2 million position. Other investors bullish on the company included Citadel Investment Group, Adage Capital Management, and OrbiMed Advisors. In terms of the portfolio weights assigned to each position, Unio Capital allocated the biggest weight to Intuitive Surgical, Inc. (NASDAQ: ISRG), around 3.45% of its 13F portfolio. Rock Springs Capital Management is also relatively bullish on the stock, designating 3.12 percent of its 13F equity portfolio to ISRG.

1. NVIDIA Corporation (NASDAQ:NVDA)

NVIDIA Corporation (NASDAQ:NVDA) operates as a visual computing company worldwide. It operates in two segments, GPU and Tegra Processor. The company has a market capitalization of $261.104bn. NVIDIA (NASDAQ:NVDA) has been one of the best performers in the U.S. stock market for the last few years. This year alone, shares of the company have increased by 77%, 150% in the last 12 months, against its industrys 45% climb. The stock, which was around $20 at the beginning of 2015, currently trades at $424.56 (July 30), representing a more than twenty-fold jump. The company recently surpassed Intel (NASDAQ:INTC) to become the largest U.S. semiconductor maker.

Based on this performance, it is no surprise that the stock is in the portfolio of 95 hedge funds. Fisher Asset Management and GQG Partners held the largest equity positions in NVDA in our database at the end of March.

Disclosure: None. This article is originally published at Insider Monkey.

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Top 5 Robotics and Artificial Intelligence Stocks To Buy According to Hedge Funds - Yahoo Finance

An exam watchdog has told pupils the statistical modelling being used to standardise their A-level and GCSE results is for their own good.

The new algorithm was created because of concern that relying solely on grades predicted by teachers could lead to inflated and unreliable results.

British qualifications are a popular choice for students in the UAE, with 91 schools offering A-levels, says WhichSchoolAdvisor, a reviewer of leading independent schools.

They are typically taken at ages 16 and 18, respectively.

Schools in May sent exam boards the grades they anticipated that pupils would have achieved had formal assessments not been cancelled because of the spread of Covid-19, along with ranking orders for them in each of their subjects.

Ofqual, the exams regulator in England, has since said that the boards were standardising the information they had received, making adjustments to grades where needed to bring consistency to teacher judgements across all schools and colleges, and to make sure results are comparable with previous years.

This is in your interest and those of all students, and means that you, universities, colleges and employers can have confidence in results this year, it said in guidance for pupils posted online this week.

The latest statement comes after Ofquals annual summer symposium for stakeholders, which covered in detail the exceptional arrangements in place for awarding grades this year.

It explained the variety of tools that would be used in the modelling to compute final grades, including historical results achieved by schools. The results will be published for A-levels on August 13 and on August 20 for GCSEs.

Jeff Evans, the director of Learning Key Education Consultancy in Abu Dhabi, said confidence could be shaky if the results release earlier this month of the International Baccalaureate, a rival education programme for which exams were also cancelled, was any gauge.

Mr Evans said that there had been angry responses after some grades were far lower than predicted.

Its a concern really because having seen what happened with the IB exams, the IB scores were drastically downgraded in many cases parents and students will be very anxious, especially with university places depending on a one-grade difference sometimes, he said. Its a pretty unprecedented situation.

One significant bone of contention is the use of mock exams in factoring the final grade, he said. January mock exams are notoriously unreliable as a predictor of final results, Mr Evans said, because students often bump their marks up by a couple of grades when they sit the real A-levels and GCSE several months later.

There are also fears that such a system could disadvantage poorer pupils and those from black, Asian and other ethnic-minority backgrounds, who are more likely to attend worse-performing schools.

Concern was raised last month in a report by a committee of British MPs that wealthier pupils may benefit more from this kind of assessment.

The committees chair, Robert Halfon, said it was far from convinced that the appeals system would be fair.

Ofqual rebutted the claim, saying the expectation was that the majority of grades would be identical to or within one grade of those predicted by teachers.

A few days later it modified its position, releasing a statement that declared some teachers had been optimistic in their predictions but not uniformly so. Others had not been optimistic at all.

Simply using the CAGs [centre assessment grades] to determine final grades would have been unfair, it said.

Ofqual also said that appeals would still be allowed but only if there had been an error in the process. You cant appeal just because you do not agree with the grade you received, the new guidance said.

Those who wished to improve any of their grades would also have an opportunity to take exams in the autumn.

WhichSchoolAdvisor said it hoped those with a legitimate causes for concern would have their grievances addressed promptly.

Updated: August 2, 2020 08:57 PM

Link:
Artificial intelligence used to grade GCSE and A-level exams - The National