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(Photo : Bigstock) AI Learning and Artificial Intelligence Concept - Icon Graphic Interface showing computer, machine thinking and AI Artificial Intelligence of Digital Robotic Devices

The nearshoring technology industry is finding a rapid growth in demand from North American companies for engineers and data science services related to the advances that are coming through the ongoing artificial intelligence (AI) revolution. Companies find high value in working on new and sophisticated applications with nearshoring firms that are close in proximity, time zones, language, and business culture.

In recent years, the costs involved in offshoring have increased in relative comparison to nearshoring costs. Additionally, tech education opportunities in the Western hemisphere have become more advantageous. Western countries have far fewer holidays and lost workdays than in offshore countries as well. In this article, NearShore Technology examines current AI trends impacting nearshoring.

AI has been an active field for computer scientists and logicians for decades, and in recent years hardware and software capabilities have advanced to the stage allowing for the actual implementation of many AI processes. In general, AI describes the ability of a program and associated hardware to simulate human intelligence, reasoning, and analysis of real-world data. Logical algorithms are allowing for increased learning, logic, and creativity with AI processes. Increased technological capabilities are allowing AI to process information in quantities and with perceptive abilities that are beyond traditional human powers. Many industrial processes are finding great utility from machine learning, an AI-based process that allows technology systems to evolve and learn based on experience and self-development.

The huge tech companies that mainly focus on how customers use software programs are leading the way in AI development. Companies like Google, Amazon, and Facebook are positioning immense resources to advance their AI processes' abilities to understand and predict customer behavior. In addition to tech and retail firms, healthcare, financial services, and auto manufacturers (aiming at a future of autonomous cars) are all committing to developing effective AI tech. From routine activities such as customer support and billing to more intuition-based activities like investing and making strategic decisions, AI is becoming a central part of competing in almost every industry.

AI development requires experienced and skillful software engineers and programmers. The ability of an AI application to operate effectively is dependent first on the quantity and quality of data that it is provided. Algorithms must be able to perceive relevant data and also to learn and improve based on the data that is received. Programmers and engineers must be able to understand and facilitate algorithm improvement over time, as AI applications are never really completed and are constantly in development. Programmers must rely on a sufficient number of competent data scientists and analysts to sort and identify the nature and quality of information processed by an AI application to provide a meaningful understanding of how well the AI is functioning. The entire process is changing and progressing quickly, and the effectiveness of AI is determined by the abilities of the engineers and programmers who are involved.

Historically, many traditional IT services have been suited for offshoring. Most traditional IT and call center support services were routine, and the cost-efficiency of offshoring these processes around the world made economic sense in many situations. When skilled programming and data science are not a requirement, offshoring has had a place in the mix for many local companies. However, the worldwide shortage of skilled engineers and data scientists is most prevalent in the parts of the world normally used for offshore services.

Nearshoring AI technology development allows local companies to have meaningful and real-time relationships with programmers and data specialists who have the requisite skills needed. These nearshore relationships are vital to the ongoing nature of AI development.

Among the most important considerations of a successful nearshoring AI relationship are examining the actual skill and education of the nearshore firm's workers. A nearshore provider's team should be up to date with the latest technology developments and should have experience and a history of success in the relevant industry. As a process that depends on natural language use, it is important that AI developers are native or fluent speakers of the client company's language. Working with a nearshore firm that is proximately near in time and place also helps the firm to properly understand the culture and needs of a company's market and customers. A nearshore firm working on AI processes should feel like a complete partner and not just another outsourced provider of routine tasks.

NearShore Technology is a US firm headquartered in Atlanta with offices throughout North America. The company focuses on meeting all the technology needs of its clients. NearShore partners with technology officers and leaders to provide effective and timely solutions that fit each customer's unique needs. NearShore uses a family-based approach to provide superior IT, Medtech, Fintech, and related services to our customers and partners throughout North America.

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NearShore Technology Talks About the Impact of Artificial Intelligence on Nearshoring - Science Times

One structure on the dwarf planet Ceres made big news but there is a hitch. It seems that the square-shaped form inside a larger triangle, located in a crater. Everyone else saw it, but the use of artificial intelligence might be a square peg not fitting a round hole. This remark by a Spanish neuropsychologist is questioning the veracity of depending on AI, which might be unsound by SETI.

Ceres is located in the main asteroid belt, a dwarf planet, and the biggest object too. One of its craters, Occator had bright lights which lead to several ideas of what it was. Nasa sent the Dawn probe to go close enough to capture visual evidence of what these lights were and solve the mystery. These lights were from volcanic ice and salt eruptions, nothing more.

It gets more interesting as researchers based in the University of Cadiz (Spain) have examined images of these spots. Areas like them are called Vinalia Faculae, in an area where geometric contours are very evident for observers. It now serves as a template to compare how machines and humans perceive images on planetary surfaces in general. Tests like these will show artificial intelligence can see technosignatures of other lifeforms besides human-civilization.

During the test, more than one individual saw the squarish shape in Vinalia Faculae, and it was a perfect chance to test artificial intelligence on a human. Subjecting a human subject with what AI sees, is a comparison to see the result. In searching for ETs, radio signals aren't the only consideration but also captured images not like before.

To see further what their hypothesis would bring about. These neuropsychologists made more modifications from the previous experiments to dig deeper by adding another layer to it. Another batch of volunteers was conscripted, but this time were amateurs in astronomy to analyze what they see in the Occator image.

By comparison to the artificial vision system that is grounded on the convolutional neural networks (CNN), an AI taught to see squares and triangles to identify them. From this point on, the experiments got interesting as it progressed.

Researchers ran the experiment and this what the people saw, some peculiarities were observed, as the images were perceived.

a. AI and people saw the square structures and did not miss it.

b. Another thing is the AI did not fail to notice the triangle as well.

c. Whenever the triangle was pointed out to people, more mentioned seeing it.

d. Visually the square was inside the triangle as it was visually represented too.

This is what the neuropsychologists drew from the results of the experiment on the "amateurs". It was published in the "Acta Astronautica journal" for reference.

a. The application of artificial intelligence for use in finding ETs is not as foolproof. Just like human intelligence the AI can be mistaken, confused and make false perception as well.

b. AI can be applied for some tasks to find technosignatures and ETs in some exceptions. Overall, AI will not be implemented but with caution, especially in SETI.

c. The presence of biases in the programming of AI is that of their creators, which is unavoidable. The best move is to study artificial intelligence, when under human stewardship.

Originally posted here:
Artificial Intelligence Suffers from The Biases of their Human Creators, that Causes Problems Searching for ET - Science Times

The Union Budget 2020 will be reported by the Central Government on 1 February 2020. While a few expectations are being communicated by industry pioneers, experts as well as students, what the government really thinks about must be resolved one week from now when the budget is given. In the meanwhile, business expectations on the Union Budget 2020 keep on pouring in.

The Union Budget 2019 of India had claimed Artificial Intelligence to be high on the agenda in the digital segment of the Budget. This declaration was huge given that China has been consistently building an ecosystem to fuel its aspiration to turn into a world leader in AI by 2030.

As indicated by most industry leaders, what India needs is a move and allocation of assets to fill this critical gap and set the groundwork across different businesses. Along these lines, this time the business is expecting that the finance minister will announce satisfactory assets on reskilling, education, ed-tech to enable the youthful population to have occupations that will be made with tech disruption and move away from ones which may soon become out of date.

The government can report AI grand challenges that are available to teams from the scholarly world and industry that include takes care of a significant issue for India. The governments job right now is to give a crisp problem definition, give access to the data and obviously give a decent cash prize. Such AI grand challenges will bring about significant issues getting tackled, new companies and occupations, and catch the countrys creative mind and be a driving force to the field of AI.

An up skilling fund is the need of the hour today to fight the skills gap made in India by emerging technologies, for example, AI/machine learning. Each business should be ordered to give a learning budget to help their employees consistently up skill and this consumption ought to be repaid to the business through the up skilling fund dispensed as a tax rebate. A corporate commitment towards upskilling boosted by the government will guarantee that HR in the nation are skilled in developing innovations/hot skill areas while energising the workforce and killing all feelings of trepidation for the future.

For India to have a $5 trillion economy, the young have a key role to carry out in empowering this objective. The advantage of the youth dividend should be channelized and empowered to make the nation famous. Quality education is significant, particularly in the rising fields, for example, artificial intelligence, big data, virtual reality and machine learning separated from the management and services in established segments.

Read more from the original source:
Expected Artificial Intelligence advancements with Union Budget 2020 - ELE Times

The first phase of the UNOSAT Challenge has just ended. The UNOSAT Challenge is the important Phi-Unet (ESA) contest for UNOSAT (United Nations) in partnership with ESA, RUS COPERNICUS, UNOSAT and with the technical support of CERN openlab.

The aim of the contest is to put artificial intelligence and Earth Observation data at the service of a humanitarian cause: support the Iraqi government in planning reconstruction activities.

71 teams of candidates (companies/startups and students) joined the competition.

In the first phase, candidates were asked to create an artificial intelligence model to identify urban areas in some Iraqi territories, working on data provided by ESA and the German Space Agency (DLR).

At the end of this phase, 5 teams were selected. These teams will enter Phase 2 and will continue in the competition.

The selection was made through an innovative artificial intelligence system for an automatic evaluation (quantitative criterion) of the projects together with the technical opinion of a jury of 21 experts coming from the prestigious partner organizations (qualitative criterion).

The AI evaluation system was developed by the Phi-Unet Team.

In addition to the 5 winners, the best student of the first phase was given the possibility of a traineeship in UNOSAT in Geneva.

The five winning teams of the first phase will have the opportunity not only to win a monetary prize but also to work on VHR (Very High Resolution) material provided directly by UNOSAT with the technical support of CERN openlab to build an artificial intelligence model that can extract automatically the building footprints in Iraq.

This request comes from a United Nations fund that supports the Iraqi government in the 2020 census, a precious source of information for planning reconstruction and development activities in the territory.

Related LinksUNOSAT ChallengeEarth Observation News - Suppiliers, Technology and Application

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Artificial intelligence to rebuild Iraq via second phase of the UNOSAT challenge - Space Daily

Super Predictor

You can probably walk up to any football fan right now and get their opinion on which team will win Sundays Super Bowl LIV.

But if youre looking for a really educated guess on the games outcome, youll want to ask Stanford computer scientist Louis Rosenberg, thefounder of Unanimous A.I., a startup that combines the opinions of a lot of humans with artificial intelligence to make remarkably accurate predictions.

In nature, many species exhibit something called swarm intelligence, meaning that they make smarter decisions as groups than as individuals in other words, a flock of birds or a school of fish is smarter than a single bird or fish.

The idea behind Unanimous A.I.is to let well-informed humans create their own swarm intelligence. As a group, they can then answer questions, reach decisions, or make predictions with a greater accuracy than any one knowledgable person alone.

In laymans terms, we build super-intelligent hive minds by connecting groups of people over the internet, Rosenberg told Digital Trends, enabling them to think together as real-time systems moderated by A.I. algorithms.

In studies, Unanimous A.I.s system was more accurate than individual experts at making medical diagnoses, forecasting financial trends, and even predicting Oscar winners.

Its Sportspicker A.I. managed to beat the spread in seven of the 10 playoff games this season. As for Super Bowl Sunday, the hive mind says the smart money is on the Kansas City Chiefs to beat the San Francisco 49ers.

READ MORE: According to advanced swarm A.I., this is who will win Super Bowl LIV [Digital Trends]

More on hive minds: A Swarm Intelligence Correctly Predicted TIMEs Person of the Year

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Hyper-Intelligent AI Hive Mind Claims to Predict Super Bowl Winner - Futurism