Mediaboss Marketing

LONDON--(BUSINESS WIRE)--The artificial intelligence-as-a-service (AIaaS) market is expected to grow by USD 15.14 billion during 2020-2024, according to the latest market research report by Technavio. Request a free sample report

The growing adoption of cloud computing services across the globe is increasing the adoption of cloud-based applications that can be used by multiple end-user industries. The inherent benefits of cloud computing such as minimal cost for infrastructure, scalability, reliability, and high resource availability have driven enterprises to adopt cloud-based solutions. This is expected to accelerate the adoption of cloud-based applications through a service model. With the rise in the adoption of cloud-based services, vendors in the market have started offering cloud-based AI services for the easy management of data. For instance, SAP offers AI capabilities integrated with its cloud-based ERP system called S4/HANA with the aim of supporting business processes such as sales, finance, procurement, and supply chain. Thus, the growing cloud adoption will drive the growth of the market during the forecast period.

To learn more about the global trends impacting the future of market research, download a free sample: https://www.technavio.com/talk-to-us?report=IRTNTR41175

As per Technavio, the increasing integration of AIaaS with blockchain will have a positive impact on the market and contribute to its growth significantly over the forecast period. This research report also analyzes other significant trends and market drivers that will influence market growth over 2020-2024.

Artificial Intelligence-As-A-Service (AIaaS) Market : Increasing Integration of AIaaS with Blockchain

Blockchain technology is integrated with AI applications to manage decentralized records and reduce human error as well as operating costs. Moreover, it can streamline, automate, and create transparency in the sharing of absolute records. Some of the advantages of integrating AI application with blockchain technology include improved traceability, real-time tracking, reduced fraud, automated data flow, and reduced paperwork. Thus, enterprises are partnering with vendors in the market to integrate blockchain-based applications to enhance transparency and efficiency. For instance, in October 2019, Global Container Terminals (GCT), a container terminal operator in North America, joined Maersk and International Business Machines to integrate TradeLens, a blockchain shipping tool, in a bid to enhance transparency and efficiency.

Factors such as the growing number of acquisitions and partnerships, and increasing investments in AIaaS by retail end-users will have a positive impact on the growth of the AIaaS market value during the forecast period, says a senior analyst at Technavio.

Register for a free trial today and gain instant access to 17,000+ market research reports

Technavio's SUBSCRIPTION platform

Artificial Intelligence-As-A-Service (AIaaS) Market: Segmentation Analysis

This market research report segments the artificial intelligence-as-a-service (AIaaS) market by end-user (retail and healthcare, BFSI, telecommunications, government and defense and others), and geography (North America, APAC, Europe, South America and MEA).

The North American region led the artificial intelligence-as-a-service (AIaaS) market in 2019, followed by APAC, Europe, MEA and South America. During the forecast period, the North American region is expected to register the highest incremental growth due to factors such as the high adoption of cloud, AI, ML, and big data analysis to draw business insights.

Technavios sample reports are free of charge and contain multiple sections of the report, such as the market size and forecast, drivers, challenges, trends, and more. Request a free sample report

Some of the key topics covered in the report include:

End-user

Geographic Segmentation

Market Drivers

Market Challenges

Market Trends

Vendor Landscape

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Read more:
Global Artificial Intelligence-as-a-Service (AIaaS) Market 2020-2024 | Growing Adoption of Cloud Based Solutions to Boost Market Growth | Technavio -...

Artificial intelligence is getting progressively widespread, influencing all aspects of society even Sonic drive-ins are intending to implement artificial intelligence to give better customer support. Obviously, every time another development shows up in the domain of AI, fears emerge with respect to its potential to supplant human jobs. While this is a truth of adapting to a more tech-driven society, these apprehensions will in general disregard the collaborative and job-creating characteristics that AI will have later on.

For as far back as barely any years weve seen big data and machine learning take even more a foothold in organizations, with many accepting the era of artificial intelligence (AI) is here. What is clear is that with advances being made on a practically regular schedule now, organizations need to plan for an immeasurably unique future. However, so as to take advantage, a few organizations may need to make a dramatic adjustment by the way they work.

Right now, for some organizations, AI and big data are seen such that constrains the potential they bring to the table. They are often observed as something that can help cut operational expenses, instead of as a crucial methodology for creating increases in profitability, output and improved assurance over the corporate direction. All together for AI and big data to be fruitful, organizations must consolidate them with business ability and insight making it something the C-suite cant overlook.

The rapid progression of data platforms and their abilities has seen analytical models progressively being utilized to display complex business scenarios for planning, operations, investment and innovation. Organizations keep on moving to data-driven decision making at all levels in the enterprise as data streams, processing and resulting insights become omnipresent. Given the availability of these technological capabilities, the critical question is the manner by which to make progress with these toolsets.

Before, moderately scarce skills were required to perform statistical analysis. Todays data ecosystems and platforms, however, can without much of a stretch encourage connection with sources, wrangling the information and afterwards structure, store and process with the elasticity of resources. Being on-demand in the cloud, these capacities encourage experimentation and ad hoc utilize that can deliver quick outcomes if you know the abilities, dangers and have the individuals with the knowledge and experience to utilize them.

While AI may not be granted decision-making capabilities for pivotal business assignments, its capacity to give solid, error-free data is as of now prompting imperative insights that totally change business operations.

Artificial intelligences automation abilities imply it is progressively being utilized to streamline unremarkable tasks and give laborers more opportunity for high-level activities. This can make organizations progressively effective by bringing down operating expenses and improving profitability. At the end of the day, as AI keeps on advancing, it will assist us with improving our own jobs.

However, the greatest potential for AI originates from machine learning.

As AI gains from new data inputs, it turns out to be progressively ground-breaking and better ready to help with increasingly complex tasks and algorithms, further growing opportunities for collaboration and increased efficiency. Machine learning is helping AI applications better comprehend a more extensive scope of guidelines, and even the context wherein a request is made.

This will prompt considerably faster and increasingly effective outcomes, and assisting with conquering normal issues we see today, for example, automated customer service systems being not able to explain solve complaints or requests. Indeed, even as these systems grow more developed, but, there will, in any case, be numerous instances where human interaction is expected to accomplish the ideal goals.

The pace of technological change is faltering and will just continue to gather pace, making new science, new systems, new organizations and new products. The ability to recognize and afterwards fuse the best solution for business and at the right time to expand advantage is a significant challenge. No place is this more the case than in the AI and big data area, where several start-ups are contending to be the next business pioneers.

Organizations must guarantee they have a well-structured architecture framework that empowers CIOs to respond with the flexibility required to join the new and replace the old. Along these lines, should something be seen not as working or a superior solution is found, the leaders can choose to evacuate or supplant it with something that may be a superior fit.

As AI applications become progressively intricate and more ingrained in everyday life, there will likewise be an increased requirement for people who can clarify the discoveries and decisions produced by a machine.

Supervision of AI applications will likewise be important to ensure that undesirable results, for example, discrimination and even bigotry are recognized and dispensed with to prevent harm. Regardless of how smart AI becomes, it will keep on requiring human guidance to discover new solutions and better satisfy its intended function.

Despite the fact that AI offers boundless opportunities for innovation and improvement, it wont have the option to achieve its full potential on its own. A community future will see programmers, engineers and everyday consumers and workers all the more completely integrating AI into their daily lives.

Read more here:
Integration of Data and Artificial Intelligence - Analytics Insight

Today we live in the information age, and access to information is unlimited. And that produces the paradox of misinformation. Thats why its more important than ever to have someone to trust, with access to truthful information and advanced tools for any activity related to the investment. This is the case of worldmarkets.com with its investment based on trading with AI.

Today, the most interesting feature of WorldMarkets is, without a doubt, its trading system based on artificial intelligence (AI). It started as a gold and silver price monitoring system, and they have evolved it over time until it became a complete system.

With their AI tool they can help their clients to invest without having to spend hundreds of hours searching for the right utility and potentially investible assets.

The process is quite simple, first you have to create an account in WorldMarkets. You should keep in mind that, being a real company with licenses to operate, they have certain limitations by countries (international embargoes to countries like North Korea, for example). Then the deposit is made in the desired currency, admitting a lot of means of payment, which include traditional currencies and the most important digital currencies, of course Bitcoin and some more.

Once we have a balance in our account, we have to configure a couple of options such as the level of risk and the moment our money will begin to be operated by the artificial intelligence (AI) based trading tool. We can stop it at any time and withdraw the profits whenever we want.

Two of the most interesting features of this trading system is that we have operating compound interest from the first moment (the benefits begin to be automatically reinvested as soon as they are collected, so that they generate more benefits on them). The other interesting feature is that WorldMarkets will only charge you commission on benefits, operations that do not yield benefits will have no commission.

When you talk about investment, the main characteristic in which potential investors are focused on is, obviously, the profitability that a system or product is capable of producing. And this is one of the great strengths of the system: its long-term profitability.

The AI trader operates with artificial intelligence 24 hours a day and 7 days a week, identifying satisfactory operations or arbitrations between exchanges.

The system began operating in February 2017 and today, when 3 years of system life are reached, we have an average return of 21.77% per month. A very high and very interesting result, since it barely has months in red, and the months in green weigh much more in the total.

With these figures, results (with compound interest) of + 481% during 2017, + 647% during 2018 and + 718% during 2019 have been consolidated.

The big difference that WorldMarkets offers us with its automated trading system with AI is that the results are audited and verified by external companies, having a monthly report with the operations and results of the corresponding month. This increases customer confidence through transparency.

Security is one of the main concerns of WordMarkets, so the access account is protected with an encryption system, 2FA access and all kinds of modern protections. But, in addition, the trading operation itself is also protected against system failures, since it has implemented scientific and statistical methods to control the risk margins of operations and thus protect the profitability and duration of the entire system.

The other great advantage that WorldMarkets offers us is its generous affiliation system. By which we can act as ambassadors for the company, since they share with us 50% of the commissions generated by a client that we have brought to the platform. Recall that WorldMarkets only charges commission for trading operations that are beneficial to the customer, so it will be with those operations with which we will prosper all the members of the system, thus collaborating with it to be sustainable and profitable over time.

With their long experience in the bullion market, they offer us to buy and sell coins or bullion of the main raw materials and precious metals. In addition to remote investment (without owning the good) and even vault services: a vault or remote safe where your gold bars are stored in exchange for a small commission.

They also allow us to operate in the cryptocurrency market through their associate BitMex.

Finally, and as a sign that they are a very complete portal, they allow us to train in the world of trading at no cost with an interesting video section. Remember: information is power.

If you are looking for an easy and profitable investment intermediation service, WorldMarkets is a very interesting idea. And especially through its flagship product: the profitable investment vehicle based on AI for trading.

See the original post here:
WorldMarkets Continues With the Success of Its Trading Artificial Intelligence - Live Bitcoin News

Over the past decade, the belief that artificial intelligence could solve the complexities of the stock market has spread like a wildfire. The notion that humans lack the capacity and capability compared to machines, who will, without fail, consistently beat the market over time. By simply programming a machine, it will produce the ultimate formula making you filthy rich in the process. A radical change in society where anyone can make money, but not just a stable income: a modest fortune.

Unfortunately, though, this is a mere fantasy.

Theres a major flaw in algorithms built solely to predict future market moves: they dont. They only respect the technical aspects of an asset by taking into account past price movements, avoiding any consideration for future fundamentals. Any veteran trader will tell you the market isnt there to give away free money. Instead, its a competitive environment punishing anyone or anything who tries to make a quick buck by trading on reactionary information already priced in.

Technical analysis alone will not make you money. In fact, the myth that it does has fueled an entire industry which preys on the vulnerable: As the homepage of many online brokerage websites illustrates,up to 96% of foreign exchange traders have fallen for the trickery. The truth about the brokerage industry is it makes money when its clients lose. So when your broker offers you a plethora of trading algorithms to choose from, the alarm bells should be ringing.

Still, you may fall for the con, because the trickery itself is seductive: Let the algorithms do everything for you, sit back and relax until you can retire. All the algorithm has to do is choose the right direction: either buy or sell, right?

Wrong.

In reality, feeding an algorithm with data based purely on technicals is the equivalent to putting on a blindfold and aiming at a dartboard. You hit the board 1 out of 10 times, but the rest hit the wall.

The buy or sell illusion isan anchoring effect: a cognitive bias discovered by the renowned psychologistsDaniel KahnemanandAmos Tverskywhere your mind tricks you into believing your chances of winning are much higher than they actually are, due to being presented with a binary choice.

The stock market is one of the most complex systems weve created as a species and it cannot be beaten all the time. Its the collective decision making of not just humans, but also machines, algorithms, and algorithms predicting what other algorithms are going to do next an infinite loop of complexity. And when you multiply the probability of all these inputs together, the chance of succeeding is miniscule. Realistically, your odds are way less than 50%, and, in some cases, even less than 1%.

Its clear by now that the complexities of the market can overwhelm a human, but they can also overwhelm machines as they have yet to counter massive market fluctuations. When they do occur,operators are forced to switch off the algorithmsand allow human traders to take over. The modern market environment has become so dynamic, machines have failed to protect against huge standard deviation moves associated with black swan events.

For example, in 2015, the foreign exchange markets were a non-volatile asset class. All the major G10 currency pairs were rangebound, moving a few hundred pips here and there. For the EUR/CHF currency pair it was a quiet start to the year until January 5th when the Swiss National Bank (SNB) unexpectedly abandoned its cap of 1.20, causing a colossal intra-hour move of 20%. In a matter of minutes,hedge funds blew up, andretail traders lost a fortune, but the machines did too.

Not only are machines incapable of predicting a black swan event, but, in reality,they are more likely to cause one, as traders found out the hard way during the2010 flash crashwhen an algorithmic computer malfunction caused a temporary market meltdown.

Ultimately, A.I is doomed to fail at stock market prediction. Beating the stock market over time, however, is possible. The solution lies with us because we humans have an edge. We have the ability to make informed decisions by analyzing future catalysts of an asset, and the reasons why they will move the price up or down a strategy artificial intelligence has yet to beat us at.

Success in trading, like in any other discipline, requires hard work and extensive research, but this only results in having a slightly better chance of succeeding. With the best traders only getting up to half their trades right, this shows that if we humans have failed to decipher our own collective minds, then A.I doesnt have a chance.

Here is the original post:
Why Artificial Intelligence Will Never Beat the Stock Market - Traders Magazine

Radiology is one of the most essential fields in clinical medicine. Experts in this field are specialists in deciphering and diagnosing disease based on various imaging modalities, ranging from ultrasound, magnetic resonance imaging (MRI), computerized tomography (CT), and x-rays. Studies have shown that the use of radiology in clinical practice has exponentially grown over the years: at the Mayo Clinic, between the years 1999 to 2010, use of CT scans increased by 68%, MRI use increased by 85%, and overall use of imaging modalities for diagnostic purposes increased by 75%, all numbers that have likely continued to rise, and indicate the sheer demand and growth of this robust field.

A unique proposal that has become prominent over the last few years to help alleviate this increased demand is the introduction of artificial intelligence (AI) technology into this field. Simply put, the premise of AI as an addition to the practice of radiology is straightforward, and has been envisioned in two main ways: 1) a system that can be programmed with pre-defined criteria and algorithms by expert radiologists, which can then be applied to new, straightforward clinical situations, or 2) deep learning methods, where the AI system relies on complex machine learning and uses neural-type networks to learn patterns via large volumes of data and previous encounters; this can then be used to interpret even the most complicated and abstract images.

Variety of body scans.

However, while much of the theoretical basis for AI in the practice of radiology is extremely exciting, the reality is that the field has not yet fully embraced it. The most significant issue is that the technology simply isnt ready, as many of the existing systems have not yet been matured to compute and manage larger data sets or work in more general practice and patient settings, and thus, are not able to perform as promised.Other issues exist on the ethical aspects of AI. Given the sheer volume of data required to both train and perfect these systems, as well as the immense data collection that these systems will engage in once fully mainstream, key stakeholders are raising fair concerns and the call for strict ethical standards to be put into place, simultaneous to the technological development of these systems.

Furthermore, the legal and regulatory implications of AI in radiology are numerous and complex. There are significant concerns in the data privacy space, as the hosting of large volumes of patient data for deep learning networks will require increased standards for data protection, cybersecurity, and privacy infrastructure. Additionally, given that AI systems will act as an additional diagnostic tool that must be accounted for in the patient encounter, legal frameworks will be required to fully flush out and navigate where liability falls in the case of misdiagnosis or medical negligence. Will this become an issue for the product manufacturer, or will there be a dynamic sharing of the responsibility by multiple parties? This will depend significantly on the amount of autonomy afforded to these systems.

However, radiologists must remain central to the diagnostic process. While AI systems may be able to detect routine medical problems based on pre-defined criteria, there is significant value provided by a trained radiologist that software simply cannot replace. This includes the clinical correlation of images with the physical state of the patient, qualitative assessments of past images with current images to determine progression of disease, and ultimately the most human aspect of medicine, working with other healthcare teams to make collaborative care decisions.

Using a human brain model to interpret MRI scans.

Indeed, there are significant potential benefits to the mass integration of certain AI systems into the practice of radiology, mainly as a means to augment a physicians workflow, especially given increasing radiology demands in clinical medicine. With some reports citing an expected rise in the use of AI in radiology by nearly 16.5% within the next decade, significant complexities remain unaddressed. However, these issues will ultimately need to be resolved in order to achieve a comprehensively capable and ethically mindful AI infrastructure that can become an integral part of clinical radiology.

Read the original:
Artificial Intelligence Is Not Ready For The Intricacies Of Radiology - Forbes