Category Archives: Artificial Intelligence
The hits and misses of using Artificial intelligence for recruitment – Livemint
Artificial intelligence is making huge strides and has been occupying some of the best minds of this century, but the hype around it is just as massive. Artificial intelligence is entering everyday lives and products, and many of us find ourselves in positions, both in our professional and personal lives, where we need to evaluate the genuineness of claims to using AI. And if we cant separate the hype from the truth, wed end up spending money on fake products and services.
Over the years that Ive spent with startups, Ive come across both genuine AI products and fakes. Ill start with the ones that truly solved problems using AI.
A few years ago, one of the co-founders of Liv.ai, a Bengaluru-based AI start-up, met me and demonstrated their product that used natural language processing (NLP) to convert speech to text in multiple Indian languages. Converting speech to text in multiple languages was a hard problem to solve. I was a bit skeptical at first, but when I saw the product, I was quite blown away. Flipkart acquired it and built a shopping assistant, Saathi, with text and voice interface to support shoppers in the smaller towns.
Facial recognition is another problem that has been solved and has wide applications that touch everyday lives, including unlocking ones smartphone. Work is in progress for image recognition applications in other fields, including in horticulture.
And now, I come to what I call fake products riding the AI wave. A vendor once approached us claiming their product could predict criminal tendency in an individual with an accuracy of 60%, and suggested we use this tool to evaluate our delivery boys. This means there is a 40% probability that it would classify someone with no criminal tendency as one with a criminal tendency. Do you need anything else to decide whether you should pay this vendor and run all your new hires through a test like this?
Another AI vendor once confidently bragged to us that their tool could look at a job description, evaluate 100 CVs and pick the best five suited for the job. When we asked, How?, they resorted to deep jargon: We use a deep learning algorithm. When we tested the tool and got it to look at 100-odd CVs and shortlist the best five, there was a zero match with what a good recruiter and hiring manager with years of experience had shortlisted.
Claims like these give AI a bad name. Arvind Narayanan, a computer science professor at Princeton, puts it more succinctly, Much of whats being sold as AI today is snake oil it does not and cannot work. Why is this happening? How can we recognize flawed AI claims and push back?"
He has classified AI into three broad buckets:
1. Areas where AI is genuine and making rapid progress like facial recognition, medical diagnosis from scans, etc.
2. Areas that are imperfect but improving like detection of spam, hate speech, etc.
3. Fundamentally dubious areas like predicting job success, recidivism, at-risk kids etc.
The last category, which is really about predicting social outcomes, is essentially the snake oil being sold to gullible users and used as a pretext for collecting a large amount of data. Users are made to believe that magical insights can somehow be extracted from large amounts of data and more the data better the insights.
Professor Narayanan writes that there has been no real improvement in the third category, despite how much data you throw at it; he further goes on to show that for predicting social outcomes, AI is worse off than manual scoring using just a few features.
In another questionable claim, Ginni Rometty of IBM said last year that IBM artificial intelligence can predict with 95% accuracy which workers are about to quit their jobs. In my opinion, using AI to predict human and social behaviour will always be flawed because human beings arent all that predictable. Theyre individualistic, and their behaviours depend on a number of factors that cant always be reduced to data points.
The protagonists of predicting social outcomes will no doubt claim that it is only a matter of time before AI gets better. I believe this is untrue.
Those who have heard of chaos theory (more commonly known as the butterfly effect) understand that small differences in initial conditionssuch as those due to rounding errorscan yield widely diverging outcomes even for deterministic systems where an approximate present cannot determine an approximate future. So, one can imagine how much more indeterminate or irrelevant the predictions would be for inherently non-deterministic systems like social behaviours and outcomes. Just as the Heisenbergs uncertainty principle places fundamental limitations at an atomic level, chaos theory places a similar limitation in areas like social outcomes.
Vested interests will always have a motive for creating the myth of being able to predict social outcomes using vast data. This myth needs to be dispelled.
T.N. Hari is head of human resources at Bigbasket.com and adviser to several venture capital firms and startups. He is the co-author of Saying No To Jugaad: The Making Of BigBasket.
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The hits and misses of using Artificial intelligence for recruitment - Livemint
Artificial intelligence is changing the world here’s how to invest – Telegraph.co.uk
This is the second part in aseries looking at the investments for the future sectors that will grow to become major industries and provide returns along the way. Part onelooks at clean energy. We will also focus on, water security, ageing populations and nutrition
"Alexa, can I make money investing in companiesthat buildartificial intelligence (AI) programmes?"
There is a lot of hype around the technology andit has thepotential to transform our lives. This naturally has led to investors approaching the sector with interest, looking to see whether they can invest in the next big technological change.
Investing in something as specific as AI is known as thematic investing or trend investing. Thisis a way of getting exposure to one niche area that is expected to expand significantly over time and therefore grow an investment.
Investing in AI is the second part in aseries looking at trend investing. Telegraph Money studies the outlook AI companies, how they would withstand a recession and what is the best way to invest for those enamoured with the sector.
AI is beginning to touch all areas of our lives, from suggesting films on Netflix to helping doctors diagnose diseases. It even interacts with us in our homes via smart speakers, which can play music and answer questionsamong an increasingly sophisticated array of "skills".
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Artificial intelligence is changing the world here's how to invest - Telegraph.co.uk
The role of Artificial Intelligence today – – VENTS Magazine
Artificial Intelligence (AI) is probably one of the branches of Computer Science that is experiencing more growth nowadays. Even though it was born more than 70 years ago, it is in a historical period where it has generated more interest because of the revolution it has caused on the market today.
Until very recently, there were limited computational capacities that made Artificial Intelligence produce very poor results on the problem being applied, which resulted in several periods of historical dissatisfaction in the industry and considerable reduction in both interests. In this case, discipline on the number of dedicated researchers.
However, in recent years Artificial Intelligence has gained enormous momentum, able to solve problems with computers that were previously thought to be impossible, reaching levels that had never been reached before. Even mobile devices benefit from research in this area, for example, through keyboard predictive text, fingerprint screen unlocking, or face detection on a frame taken by a camera.
Several reasons that have functioned as AI takeoff machines can be listed, but the democratization of computational capacity stands out with particular emphasis, especially since 2009 with the publication of the first scientific article about the massive parallelization of AI calculations using GPUs and others in 2010, to demonstrate their use in automatic recognition of handwriting, exceeding for the first time the capacity of humans in this task. In this way, Artificial Intelligence gets its name because of the ability of electronic devices to solve problems that require intelligence and that, in the traditional way (programming), cannot be solved on a computer.
Looking back, the birth of Artificial Intelligence occurred more than 70 years ago, in the hands of Alan Turing, considered the father of this discipline. In 1936 he compiled a computational model, which consisted of heads on an infinite long band that could read, write and scroll. This computational model is called a Turing machine, and it is possible to represent any computational operation, in other words, any computation can be reduced and represented by a Turing Machine. This raises the following question: If the brain exerts computational operations, can it be reduced and represented by the Turing Machine?
If this is possible, it means that operations that we consider to be intelligent can be carried out automatically, such as the detection of objects in an image, the classification of sounds, or even the proper functioning of brain awareness. We cannot assert that the latter may occur, however, there is progress in simulating or approaching intelligent behavior, which is why subfields have emerged in the fields of Artificial Intelligence such as Computer Vision (CV), Machine Learning (ML) and Natural Language Processing (NLP).
The Japans case: Matchmaking
In Japan, a country with a high level of technological development, AI has played a more important role in matchmaking. AI devices began to be used to provide a picture of a potential partner only through the touch of a hand. It seems that the intelligence will be a determinant factor in matchmaking, today and in the future. You can find more information here. It seems that Artificial Intelligence begins to have the maturity to be applied in solving problems which until a few years ago were deemed unsolvable by machines. And one important factor in this phenomenon is that AI systems can operate independently like living things. This system is able to regulate itself, act like thinking beings, and thats why the reason is called Artificial Intelligence.
In short, Artificial Intelligence is the future of humans. We as humans cannot escape this reality. All we can do is make sure it works according to human norms and ethics. Hopefully this article can provide an overview of our future.
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The role of Artificial Intelligence today - - VENTS Magazine
Evolving Relationship Between Artificial Intelligence and Big Data – ReadWrite
Find the evolving relationship between big data and artificial intelligence. The growing popularity of these technologies offers engaging audience experience. It encourages newcomers to come up with an outstanding plan.
AI and Big Data help you transform your idea into substance. It helps you make full use of visuals, graphs, and multimedia to give your targeted audience with a great experience. According toMarkets And Markets, the worldwide market for AI in accounting assumed to grow. As a result, growth from $666 million in 2019 to $4,791 million by 2024.
The critical component of delivering an outstanding pitch is taking a step further with an incredible plan of assuring success. Big data and Artificial intelligence help you contribute to multiple industries bringing an effective plan. It can directly speak to investors and your targeted audience, covering essential aspects and representing your idea in a nutshell.
According to Techjury, The big data analytics market is set to reach $103 billion by 2023, and in 2019, the big data market is expected to grow by 20%.
From transformation to the phenomenal growth AI and Big data provide you with the accessibility of relevant information. Big data holds the data from multiple sources like social media platforms, search data, and others, which can be structured or unstructured. While artificial intelligence is intelligence demonstrated by machines with the rise of natural intelligence displayed by humans.
The most exciting thing for anyone to do is to identify the problem. So to know what prevents people from reaching their goal. From the product or service you wish to obtain the targeted audiences attention, it must solve the problem of the potential customers. There can be any problem from simple to complicated for which customers need a solution.
For every problem, there is a solution. Once you have understood the problem and willing to bring change, you can clearly solve the problem in the most defined ways. Artificial intelligence is a true reflection of technology advancement. With big data, you can make full use of vital information extracting the information you need.
For every problem, there is a solution. Once you have understood the problem and willing to bring change, you can clearly solve the problem in the most defined ways. Artificial intelligence is a true reflection of technology advancement. With big data, you can make full use of vital information extracting the information you need.
One can come with accurate solutions using AI and big data. It helps in introducing a low error rate compared to humans if appropriately coded. The AI takes the decision based on data and a set of algorithms, which decreases the chance of error. Big data and AI, when used together, can really help you solve the problem by answering the potential issues and bringing an effective solution.
To solve any kind of problem, one must know about the potential market. Divide your target market into segments from whom you expect to get a positive response. It helps you do what you need to. These advanced technologies have a strong foundation with outstanding capabilities to capture the potential market. One must learn and apply these technologies to get a better result in transforming the overall experience of customers.
Capturing the target audiences attention is as important as solving the problem. Once you know how big is your potential market is, and what your target audience wants, you can use these advanced technologies to pitch and get the desired result. That is only possible if you use your segment creatively and consider creating your own identity for targeting your customer while working on your business plan.
Every industry has its own competition with a particular set of competitors. One must invest in something that can really help people and bring the best solution for them with beneficial results and stand out in the real competition.
To stay in the market and promote your service, one must invest in providing customers with alternative solutions. These AI solutions can help you increase your customer base. Give your customers the reason to choose your solution over someone elses. That reason will be the identity that you will create in the market. Build a unique solution that can help you focus on growing your business and stay ahead in the competition.
Mark your presence in the market, accomplishing specific goals that you desire to achieve and have already accomplished. Make your business a reality setting realistic goals and perform better and notable milestones to achieve greater success. The core essence of running a smooth business and getting all that you desire is accomplishing set milestones.
Accomplishing set milestones can really help you get desired results and gain positive support from the trusted and reliable model. By doing this, you can strategies your small business plan with changing times and market demand. Gain an ideal position in the market with better results and in-depth data.
Achieving a milestone can be a tough task. However, with AI & Big data, it has become possible to get predictive analysis for better results and position of control. Consider all the options that make you stand out in the competition and help you grow your business.
AI can help you analyze consumer data patterns. It can predict what users would like to pay for with the help of big data. Both these technologies are compelling to present and provides a useful result that can boost your sales and increase business revenue.
Nitin Garg is the CEO and Co-founder of BR Softech Business Intelligence Software Company. Likes to share his opinions on IT industry via blogs. His interest is to write on the latest and advanced IT technologies which include IoT, VR & AR app development, web, and app development services.
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Evolving Relationship Between Artificial Intelligence and Big Data - ReadWrite
The Evolution of Artificial Intelligence as a System – Security Magazine
The Evolution of Artificial Intelligence as a System | 2020-01-09 | Security Magazine This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more. This Website Uses CookiesBy closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
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The Evolution of Artificial Intelligence as a System - Security Magazine
Hollywood Is Using Artificial Intelligence To Pick Its Next Blockbuster – Forbes
Hollywood-based film studios are increasingly using AI as part of the decision-making process when ... [+] commissioning and producing new films. (Photo by Valery SharifulinTASS via Getty Images)
For anyone who's ever thought Hollywood's output is formulaic and tired, the movie industry may be about to get worse. Major studio Warner Bros. has signed a deal with Cinelytic, which has developed an AI-powered system that can predict the likelihood of a film's success based on such factors as actors, budget and brand.
Predictably enough, Warner Bros. will be using Cinelytic's software as part of the research process it undergoes when deciding which movies to commission. Cinelytic's platform can determine the 'value' (i.e. profitability) of an actor in any major territory and also calculate how much money a film is likely to earn in cinemas and through supplementary merchandising (e.g. DVDs).
While it obviously can't measure how good a film will be artistically, Warner Bros. will likely use it during early production phases to separate ideas likely to succeed from those that most likely aren't. This follows a run of several years during which the studio has suffered a number of high profile losses on such titles asJustice League and Pan, as well as a few instances where its output hasn't performed as well as hoped (e.g. Batman v. Superman).
And it would seem that Warner Bros. won't be the only film studio integrating AI into its decision-making processes. In fact, AI has already received a modest amount of use by studios up until now, so Warner Bros. entry is likely to open the floodgates even further.
For example, 20th Century Fox has been using a system called Merlin for several years now. In contrast to Cinelytic's platform, Merlin uses AI and machine learning (as well as big data) to match particular films to particular genres and audiences. It does this by using a computer vision system to generate a frame-by-frame analysis of movie trailers. After labelling objects and events within each trailer, it then takes the data it has gathered for one film and compares it against data for other films. It might find, say, that a given trailer most resembles films x, y and z, which were popular with female teenagers.
By comparing datasets, Merlin helps 20th Century Fox identify the ideal demographic(s) for any given film. It also helps the studio decide how it should be advertising and classifying that film, insofar as Merlin links a films trailer to genres.
Aside from Warner Bros. and 20th Century Fox, it's likely that other film studios and production companies have already turned to AI, without being open about it. For instance, Belgium-based ScriptBook uses AI to analyze a film's script and arrive at an estimation of the revenues that film is likely to earn. Not only that, but ScriptBook's platform can also provide likability scores for a film's characters, profiles of its target audience, and even its likely IMDB rating.
According to the company's CEO, Nadira Azermai, ScriptBook is already at a stage where the financial forecast it provides for each film has an 86% accuracy rate. In other words, it's already working with clients in the film industry, even if it hasn't gone public with the names of any studio or company.
ScriptBook was founded in 2015, but it's probable that other companies will emerge in the coming years, since research into the use of AI-based film prediction is still ongoing. In August, researchers from Sungkyunkwan University in South Korea revealed that they had used deep learning to train a bot to forecast the likelihood of a film's success, based this time on a textual summary of its plot. They trained this bot on 42,306 film plot summaries, in the end finding that it was best at predicting which films would be unsuccessful.
That the bot was better at weeding out 'stinkers' rather than classic films is encouraging. Because while the influx of AI into the film industry might imply that Hollywood could become even more self-plagiarizing in the future, it's possible that studios might restrict the use of artificial intelligence specifically to making sure they don't end up commissioning flops. This would potentially leave space for human decision-making and creativity to get involved in choosing between ideas more likely to succeed commercially.
And to play devil's advocate, it's possible that the use of AI might make Hollywood's output less homogenous. To take a simplified and hypothetical example, the massive success of a superhero film could conceivably create a situation where human producers end up commissioning a series of other superhero movies, even though each entry in this series goes on to enjoy diminishing returns. By contrast, an AI-based platform trained on masses of regularly updated data might be able to determine that, rather than making the next Batman or Superman film, a different kind of movie now has a chance of greater success.
That is, an AI platform might force a studio to change its artistic or stylistic direction sooner than it would have done otherwise. If this is the case, then moviegoers and cinephiles probably don't have anything to fear from AI's invasion of cinema.
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Hollywood Is Using Artificial Intelligence To Pick Its Next Blockbuster - Forbes
Machine Learning and Artificial Intelligence Are Poised to Revolutionize Asthma Care – Pulmonology Advisor
The advent of large data sets from many sources (big data), machine learning, and artificial intelligence (AI) are poised to revolutionize asthma care on both the investigative and clinical levels, according to an article published in the Journal of Allergy and Clinical Immunology.
According to the researchers, a patient with asthma endures approximately 2190 hours of experiencing and treating or not treating their asthma symptoms. During 15-minute clinic visits, only a short amount of time is spent understanding and treating what is a complex disease, and only a fraction of the necessary data is captured in the electronic health record.
Our patients and the pace of data growth are compelling us to incorporate insights from Big Data to inform care, the researchers posit. Predictive analytics, using machine learning and artificial intelligence has revolutionized many industries, including the healthcare industry.
When used effectively, big data, in conjunction with electronic health record data, can transform the patients healthcare experience. This is especially important as healthcare continues to embrace both e-health and telehealth practices. The data resulting from these thoughtful digital health innovations can result in personalized asthma management, improve timeliness of care, and capture objective measures of treatment response.
According to the researchers, the use of machine learning algorithms and AI to predict asthma exacerbations and patterns of healthcare utilization are within both technical and clinical reach. The ability to predict who is likely to experience an asthma attack, as well as when that attack may occur, will ultimately optimize healthcare resources and personalize patient management.
The use of longitudinal birth cohort studies and multicenter collaborations like the Severe Asthma Research Program have given clinical investigators a broader understanding of the pathophysiology, natural history, phenotypes, seasonality, genetics, epigenetics, and biomarkers of the disease. Machine learning and data-driven methods have utilized this data, often in the form of large datasets, to cluster patients into genetic, molecular, and immune phenotypes. These clusters have led to work in the genomics and pharmacogenomics fields that should ultimately lead to high-fidelity exacerbation predictions and the advent of true precision medicine.
This work, the researchers noted, if translated into clinical practice can potentially link genetic traits to phenotypes that can for example predict rapid response, or non-response to medications like albuterol and steroids, or identify an individuals risk for cortisol suppression.
As with any innovation, though, challenges abound. One in particular is the siloed nature of the clinical and scientific insights about asthma that have come to light in recent years. Although data are now being generated and interpreted across various domains, researchers must still contend with a lack of data standards and disease definitions, data interoperability and sharing difficulties, and concerns about data quality and fidelity.
Machine learning and AI present their own challenges; namely, those who utilize these technologies must consider the issues of fairness, bias, privacy, and medical bioethics. Legal accountability and medical responsibility issues must also be considered as algorithms are adopted into routine practice.
We must, as clinicians and researchers, constructively transform the concern and lack of understanding many clinicians have about digital health, [machine learning], and [artificial intelligence] into educated and critical engagement, the researchers concluded. Our job is to use [machine learning and artificial intelligence] tools to understand and predict how asthma affects patients and help us make decisions at the patient and population levels to treat it better.
Reference
Messinger AI, Luo G, Deterding RR. The doctor will see you now: How machine learning and artificial intelligence can extend our understanding and treatment of asthma [published online December 25, 2019]. J Allergy Clin Immunol. doi: 10.1016/j.jaci.2019.12.898
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Machine Learning and Artificial Intelligence Are Poised to Revolutionize Asthma Care - Pulmonology Advisor
Warner Bros. Will Use Artificial Intelligence to Help Decide Which Movies to Greenlight – /FILM
Update: An in-the-know source has reached out to correct some of the information in this story. Turns out that Cinelytic is only being used by Warner Bros. International as an additive tool to help select release dates, and not, as many have suggested, in any sort of major creative capacity. Our original story continues below.
The frequent tug-of-war between art and commerce means that there have long been Hollywood studio executives whose jobs include looking at analytics and trying to assess whether greenlighting a certain film will be financially beneficial to their shareholders. Now Warner Bros. is inviting artificial intelligence into the equation, because the studio has signed a deal with a company called Cinelytic to use itsproject management system and leverage the systems comprehensive data and predictive analytics to guide decision-making at the greenlight stage. Is this situation as bad as it sounds?
The Hollywood Reporter has the story, saying that Toby Emmerichs film division of Warner Bros. is going to utilize this system, which is supposed to help find patterns in the numbers that might be missed by human eyes. The platform is capable of assess[ing] the value of a star in any territory and how much a film is expected to make in theaters and on other ancillary streams, and its supposedly going to reduce the amount of time executives spend on low-value, repetitive tasks and instead give them better dollar-figure parameters for packaging, marketing and distribution decisions including release dates.
According to Cinelytic head Tobias Queisser, who invented this system four years ago, The system can calculate in seconds what used to take days to assess by a human when it comes to general film package evaluation or a stars worth. But as Thor and X-Men: First Class screenwriter Zack Stentz wrote on Twitter,the entire Marvel Cinematic Universe was built on [Jon] Favreau convincing a bunch of executives that a middle-aged actor not long out of rehab and prison, who had described himself as box office poison even during his earlier 1990s heyday, would be the perfect Iron Manthese analytics that purport to tell you which actor is worth how much in these territories are useless compared to the casting intuitions that end up creating magic onscreen.
Still, I can sympathize with this level of desperation. Its easy to see why studios would be eager to minimize risk and find a way to compete against Disney, which absolutely crushed all competition last year and became the first studio to cross the $10 billion mark in a single year (the House of Mouse pulled in$11.12 billion total worldwide). And its not like all of a sudden every movie will be chosen by an algorithm Queisser says that an AI cannot make any creative decisions and explains its real intended use in this setting. What it is good at is crunching numbers and breaking down huge datasets and showing patterns that would not be visible to humans, he said. But for creative decision-making, you still need experience and gut instinct.
Emmerich has been in this business for a long time, and anyone who expects him to just cede all creative control over to Skynet is misreading this situation. Im betting the studio will look at these AI-crunched numbers to help figure out better release dates every once in a while, and leave the real creative decisions to the people who are getting paid millions of dollars a year to make them.
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Warner Bros. Will Use Artificial Intelligence to Help Decide Which Movies to Greenlight - /FILM
Should Artificial Intelligence in Cars Be Programmed to Be Racism-Free? – Science Times
(Photo : silvawpius.wordpress.com)What are the causes of racial discrimination in artificial intelligence in cars? How does it happen and can it be avoided at all. Does AI really abstract or it is just a set of algorithms too.
When the first singularity called the "big bang" seeded the proto-universe with light and matter that was the first proto-matter into the universe today. What made the universe into what is it now, is the mysterious substance called "Dark matter". In the first few seconds of the big bang, it was so hot, when it cooled down dark matter settled. Gravity and the fundamental forces of the universe pulled all dark matter from heated halos that became everything in the universe.
Now, this dark matter is captured as visual imaged or as background radiation in the galaxy, we know today. Dark matter holds everything in the cosmos together, without it, there is no telling what can happen. Here are insights into what kinds of dark matter that the big bang cooked up, basically everything in the universe floats in a sea of endless dark matter. Kinds of dark matter as defined are warm, cold, and fuzzy, the reason is the scientist give these terms is to make them understandable. Most of the time, everyone gets lost in the play of concepts and terms. Let us begin now.
Factoid#1
Specialists from MIT, Princeton University, and Cambridge University have speculated that the proto-galaxies to later galaxies are not the same. This is because of whether it was a warm, cold, or fuzzy matter when they were formed. A simulation was designed to test the theory on dark matter formations.
Factoid#2
Most dark matter iscoldand does not mix with other matters.Warmis lighter and moves fast, not slow, a bit faster than cold DM. A new concept isfuzzydark matter which is ultralight bits and particles that heavier than an electron. Fuzzy dark matter is essentially heavier, and larger too.
Factoid#3
Most dark matter used to form halos around proto-galaxies yet to form were cold. If it was the fuzzy or warm kind, then galaxies will have trailing tails. Fuzzy universes might look striated, like harp strings.
Factoid#4
Light traveling in the cosmos can be very old, using a telescope that will tell if the dark matter is cold, warm, or fuzzy too. These three kinds of dark matter (DM) is about 85% in the universe today.
Factoid#5
Proving what dark matter is harder to do, and most guesses point at dark matter are cold mostly. And, this is what makes the superstructure of the universe and keeps it together like crazy glue,
Factoid#6
Fuzzy dark matter is totally different, and it acts like a wave throughout the universe. This wave-like dark matter is like to mix with other bits of matter, compared to cold dark matter. Galaxies formed from it will be significantly different from what it is now.
Factoid#7
The scientist is developinga new universal modelof what a fuzzy matter universe will be like. Using the James Webb Space Telescope, they will look back in time and see the first proto-galaxies as they were. Hopefully models by Mocz, Fialkov, Vogelsberger will be proven by then.
Related Article: Is Dark Matter Warm, Cold, or 'Fuzzy'? New Simulations Provide Intriguing Insights.
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Should Artificial Intelligence in Cars Be Programmed to Be Racism-Free? - Science Times
SUTD to offer new undergrad degree in design and artificial intelligence – The Straits Times
SINGAPORE - Artificial intelligence (AI) technologies can benefit designers, if they know how to harness them.
Statistical data can be used to predict an outcome a method known as predictive modelling. In urban planning for example, demand for public trains can be forecasted in order to create more efficient public transport deployment plans.
To equip students with such skills, the Singapore University of Technology and Design (SUTD) has launched a new undergraduate degree in design and AI,in anticipation of a growing demand for talents who can combine expertise in design innovation with AI technology.
The 3 -year programme - the first of its kind in Singapore - will take in students this academic year, which starts in May, SUTD said on Friday (Jan 10).
Students will be exposed to areas of design such as user interface/user experience (UI/UX), product, systems, built environment, and data-driven design.
They will also learn to use AI technologies and algorithms to produce better design and applications.
Graduates ofthis programme will be able to work as data scientists and data visualisation specialistsin industries such as urban planning, product design and telecommunications, the university said.
Established in 2009, SUTD is the fourth autonomous university in Singapore and focuses on engineering, innovation and design.
It said that the entry requirements for the new programme are the same as for its other four degrees: architecture and sustainable design; engineering product development; engineering systems and design; and information systems technology and design.
Generally, students should be competent in mathematics and the sciences, namely physics or chemistry.
Statistics provided by the university show that of the A Level students who were offered places in the university admission exercise last year, nearly all had taken mathematics at the H2 level, and eight in 10 scored at least a B.
Nearly all had also taken either physics or chemistry, or both, at the H2 Level, and nearly seven in 10 scored at least a B for either or both subjects.
SUTD president Chong Tow Chong said: "The recent announcements from Deputy Prime Minister Heng Swee Keat on the next steps in Singapore's Smart Nation journey underscorethe importance of artificial intelligence and the role it will play in bringing about social and economic benefits.
"The main goal of the design and AI programme is to equip students with the ability to create human-centred design using data analysis and machine learning, which is AI-driven," added Professor Chong.
Jurong Pioneer Junior College graduate Michael Hoon, who read H2 maths, further maths and physics, and also took a H3 physics module offered by Nanyang Technological University, is interested in the new programme.
Said the 18-year-old: "I've always been interested in maths and science since I was young, for the most part, due to exposure from school teachers and researching a lot of information online.
"Both subjects are visibly all around us and pretty much serveas the foundations of our survival and development, and being able to apply and integrate the theoretical modelling we have learnt into our daily livesis pretty interesting too."
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SUTD to offer new undergrad degree in design and artificial intelligence - The Straits Times