AI News, On Natural and Artificial Intelligence artificial intelligence

IPC Makes Strategic Investment in GreenKey Technologies, Creator of Artificial Intelligence, Natural Language Processing Technologies for Financial Services - GK

IPC , a leading global provider of secure, compliant communications and networking solutions for the financial markets community announced today that it has completed a strategic investment in GreenKey Technologies (GK), creator of natural language processing workflows for the financial markets.

IPC’s investment gives the company exclusive rights to GK’s next-generation machine learning voice technologies, uniting GK’s best-in-class markets and customer insight extraction with IPC’s trading communications expertise and cloud financial ecosystem of over 6,400 diverse market participants.

“IPC and the OTC market at large have recognized the value in our patented natural language processing solutions, and GK’s rapidly growing team looks forward to refining the exclusive synergies created by this partnership.

IPC’s GK investment follows the companies’ recent co-development efforts for a new, comprehensive set of tools and capabilities to enhance voice-to-text user workflows currently being rolled out worldwide to IPC customers.

The new ground-breaking cloud-based solution enables IPC Unigy 360 users to harvest their audio streams as structured text data to enhance front-, middle- and back-office workflows, through the integration of voice across application and instant message services.

The application can parse quotes and trades alongside conversational raw text, creating a real-time internal price data feed for organizations to easily scan and determine the most current state of multiple conversations for faster trading.

Unigy 360 unifies communications across an organization, from traders, researchers, portfolio and risk managers to surveillance and compliance professionals, technologists, settlement personnel and operations staff, with anytime, anywhere, any device access.

Applications of artificial intelligence

Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today's society.

More specifically, it is Weak AI, the form of AI where programs are developed to perform specific tasks, that is being utilized for a wide range of activities including medical diagnosis, electronic trading, robot control, and remote sensing.

Crop and soil monitoring uses new algorithms and data collected on the field to manage and track the health of crops making it easier and more sustainable for the farmers.

The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.[5]

The artificial intelligent programs can sort the information and provide the pilot with the best possible maneuvers, not to mention getting rid of certain maneuvers that would be impossible for a human being to perform.

Haitham Baomar and Peter Bentley are leading a team from the University College of London to develop an artificial intelligence based Intelligent Autopilot System (IAS) designed to teach an autopilot system to behave like a highly experienced pilot who is faced with an emergency situation such as severe weather, turbulence, or system failure.[10]

Educating the autopilot relies on the concept of supervised machine learning “which treats the young autopilot as a human apprentice going to a flying school”.[10]

The Intelligent Autopilot System combines the principles of Apprenticeship Learning and Behavioural Cloning whereby the autopilot observes the low-level actions required to maneuver the airplane and high-level strategy used to apply those actions.[11]

When students sit at their desk, their devices will be able to create lessons, problems, and games to tailor to the specific student’s needs, particularly where a student may be struggling, and give immediate feedback.

As far as the future of AI in education, there are many new possibilities due to what has been coined by The New York Times as “The Great AI Awakening.” One of these possibilities mentioned by Forbes included the providing of adaptive learning programs, which assess and react to a student’s emotions and learning preferences.

As a whole AI has the power to influence education by taking district, state, national, and global data into consideration as it seeks to better individualize learning for all.

An example of a revenge effect is that the extended use of technology may hinder students’ ability to focus and stay on task instead of helping them learn and grow.[16]

Also, the need for AI technologies to work simultaneously may lead to system failures which could ruin an entire school day if we are relying on AI assistants to create lessons for students every day.

It is inevitable that AI technologies will be taking over the classroom in the years to come, thus it is essential that the kinks of these new innovations are worked out before teachers decide whether or not to implement them into their daily schedules.

Algorithmic trading involves the use of complex AI systems to make trading decisions at speeds several orders of magnitudes greater than any human is capable of, often making millions of trades in a day without any human intervention.

Automated trading systems are typically used by large institutional investors, but recent years have also seen an influx of smaller, proprietary firms trading with their own AI systems.[17]

Its wide range of functionalities includes the use of natural language processing to read text such as news, broker reports, and social media feeds.

For example, Digit is an app powered by artificial intelligence that automatically helps consumers optimize their spending and savings based on their own personal habits and goals.

The app can analyze factors such as monthly income, current balance, and spending habits, then make its own decisions and transfer money to the savings account.[21]

Wallet.AI, an upcoming startup in San Francisco, builds agents that analyze data that a consumer would leave behind, from Smartphone check-ins to tweets, to inform the consumer about their spending behavior.[22]

This class of financial advisers work based on algorithms built to automatically develop a financial portfolio according to the investment goals and risk tolerance of the clients.

An online lender, Upstart, analyze vast amounts of consumer data and utilizes machine learning algorithms to develop credit risk models that predict a consumer’s likelihood of default.

This platform utilizes machine learning to analyze tens of thousands traditional and nontraditional variables (from purchase transactions to how a customer fills out a form) used in the credit industry to score borrowers.

“The major junctions of the system were to monitor premiums in the market, determine the optimum investment strategy, execute transactions when appropriate and modify the knowledge base through a learning mechanism.”[27]

It was able to review over 200,000 transactions per week and over two years it helped identify 400 potential cases of money laundering which would have been equal to $1 billion.[29]

Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading.

In the automotive industry, a sector with particularly high degree of automation, Japan had the highest density of industrial robots in the world: 1,414 per 10,000 employees.[30]

There are three ways AI is being used by human resources and recruiting professionals: to screen resumes and rank candidates according to their level of qualification, to predict candidate success in given roles through job matching platforms, and now rolling out recruiting chat bots that can automate repetitive communication tasks.

TextRecruit, a Bay Area startup, released Ari (automated recruiting interface.) Ari is a recruiting chatbot that is designed to hold two-way text message conversations with candidates.

Ari automates posting jobs, advertising openings, screening candidates, scheduling interviews, and nurturing candidate relationships with updates as they progress along the hiring funnel.

AI-powered engine streamlines the complexity of job hunting by operating information on job skills, salaries, and user tendencies, matching people to the most relevant positions.

Machine intelligence calculates what wages would be appropriate for a particular job, pulls and highlights resume information for recruiters using natural language processing, which extracts relevant words and phrases from text using specialized software.

Typical use case scenarios include the analysis of images using object recognition or face recognition techniques, or the analysis of video for recognizing relevant scenes, objects or faces.

The motivation for using AI-based media analysis can be — among other things — the facilitation of media search, the creation of a set of descriptive keywords for a media item, media content policy monitoring (such as verifying the suitability of content for a particular TV viewing time), speech to text for archival or other purposes, and the detection of logos, products or celebrity faces for the placement of relevant advertisements.

Another artificial intelligence musical composition project, The Watson Beat, written by IBM Research, doesn't need a huge database of music like the Google Magenta and Flow Machines projects, since it uses Reinforcement Learning and Deep Belief Networks to compose music on a simple seed input melody and a select style.

The company Narrative Science makes computer-generated news and reports commercially available, including summarizing team sporting events based on statistical data from the game in English.

Yseop is able to write financial reports, executive summaries, personalized sales or marketing documents and more at a speed of thousands of pages per second and in multiple languages including English, Spanish, French &

Boomtrain’s is another example of AI that is designed to learn how to best engage each individual reader with the exact articles — sent through the right channel at the right time — that will be most relevant to the reader.

The program would start with a set of characters who wanted to achieve certain goals, with the story as a narration of the characters’ attempts at executing plans to satisfy these goals.[55]

Their particular implementation was able faithfully reproduced text variety and complexity of a number of stories, such as red riding hood, with human-like adroitness.[57]

Power electronics converters are an enabling technology for renewable energy, energy storage, electric vehicles and high-voltage direct current transmission systems within the electrical grid.

These converters are prone to failures and such failures can cause downtimes that may require costly maintenance or even have catastrophic consequences in mission critical applications.[citation needed]

Researchers are using AI to do the automated design process for reliable power electronics converters, by calculating exact design parameters that ensure desired lifetime of the converter under specified mission profile.[62]

This prospered greatly with the Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of Artificial Intelligence, specifically in the form of Tamagotchis and Giga Pets, iPod Touch, the Internet, and the first widely released robot, Furby.

The major challenge to developing this AI is the fact that transportation systems are inherently complex systems involving a very large number of components and different parties, each having different and often conflicting objectives.[67].

UKRI Centres for Doctoral Training in Artificial Intelligence

Sixteen Centres for Doctoral Training (CDTs) in Artificial Intelligence (AI) are being supported by UKRI which will train 1,000 PhD students to exploit the potential of AI to transform the way we work and live.

Project partners are investing £78 million in cash or in-kind contributions and partner universities are committing a further £23 million, resulting in an overall investment of more than £200 million.

AAAI 2019 Conference | Thirty-Third AAAI Conference on Artificial Intelligence

The purpose of the AAAI conference is to promote research in artificial intelligence (AI) and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines.

AAAI-19 will have a diverse technical track, student abstracts, poster sessions, invited speakers, tutorials, workshops, and exhibit and competition programs, all selected according to the highest reviewing standards.

Explore the rich history of the Islands at one of the many museums or historical sites, take a hike in a lush tropical forest, or admire the unparalleled views from the conference site.

On Natural and Artificial Intelligence

ABSTRACT The current state of the art in knowledge and technology concerning natural and artificial intelligence is innovatively discussed here.

What we see, hear, touch, smell and taste gets intertwined in our minds in the form of images, sounds, sensations, smells and tastes and, as the child grows, they get associated to words, phrases and text, just as memories (sometimes distorted) of moments lived.

However, the tectum (in red or dark grey) is connected to the interior of our bodies, to the hormone levels, to the body rhythms, to breading, to heart beats and the homeostatic maintenance of our corporal metabolism.

Cognitive neuroscience and, more specifically, the Global Workspace Theory (GWT) indicates that the information flows from the unconscious (id or drives) to the pre-conscious (ego) and from that point onwards a feedback flow with the conscious (super ego) is generated [25] .

Experiments among right-handed people (that is, people whose dominating brain hemisphere is the left one, since the left hemisphere is connected to the right side of the body) have been conducted, in order to see if there is a universal neuronal language [27] [28] .

By the end of the 1990s, Hans Moravec [30] calculated the number of basic operations per second of information processing carried out by a human brain based on visual information processing.

An operation per second is equivalent, in terms of digital computers, to do one basic binary operation per second, such as adding two binary numbers or transferring a binary number from one position in memory to another one.

It is no longer possible to build smaller electrical circuitry, also called micro transistor chips (and as a consequence faster, since light takes less time to travel from one place of the micro transistor to another one), by reducing by half the size of the micro transistor, due to problems inherent to the way in which such micro transistors are built (specifically, lithography).

We are getting all kinds of different applications of the same micro transistors in all sorts of devices (smaller laptops with different and ever more consuming memory and hard drive resources, pocket size cell phones, all different sorts of Internet-related applications, and even the promise of the so-called Internet of Things―IoT).

Thus, if every personal computer has an information processing speed of 1 GHz (1,000’000,000 operations per second), we would require 100’000,000’000,000 information processing operations per second per human mind divided by 1,000’000,000 operations per second or Hz of each artificial processor, that is, we would require an AI laboratory of 100’000,000’000,000/1,000’000,000 = 100,000 personal computers properly connected in some way (still somewhat unknown for the time being) in order to compute the amount of information processing carried out by one person.

It is not feasible that normal AI laboratories around the world could properly connect 100,000 computers, not to mention buying all those computers, hosting them, and making the research affordable enough so that a lot of AI laboratories could carry out the same endeavor so that scientific exchanges could accelerate innovation pace.

We would require, at least, to double information processing speed 1000 times more (that is, 240 ≈ 1’000,000’000,000 Hz per microprocessor), so that the number of required computers could go down from 100,000 to 100 (or even 50 or 25, or maybe even just one if we allow for the consideration that human-designed digital information processing should be more efficient for not depending on evolution, having a lot of redundancies).

If it were possible to have a 256 qubits quantum computer that holds quantum entanglement for at least 200 milliseconds, it may be possible to integrate such quantum computer with a digital computer working also on 256 bits (one byte) in bandwidth.

In this way, in a still unknown form, it may be possible to represent “thoughts” using sets of bytes (characters in the ASCII standard) and build something similar to what is seen in the trilogy “The Matrix”, except that “the code” would be alphanumerical characters of one byte.

The latter is due to my hypothesis that, just like Roger Penrose considers it, the functioning of the human brain depends both on quantum as well as digital computing processes, having an internal clock of approximately 200 milliseconds between quantum entanglement losses marking consecutive states of consciousness.

Thus, if we want to build several machines with natural intelligence, all we have left to do is to expect the required technology in quantum and digital computing to advanced enough in order to reach the minimum levels previously indicated, that is, quantum computers of 256 qubits having a minimum quantum entanglement lapse of 200 milliseconds (at a reasonable price, not greater than USD $10,000) and digital computers at reasonable prices (around USD $1000 per computer) with information processing speeds of 1 THz to 4 THz (100 THz would of course be the ideal).

Since the infrastructure for such network would be, presumably, new, there is the possibility of creating the 5G network in such way that it can not only be used for the telecommunications of the future, but also for the infrastructure providing the technological hardware to create an artificial machine with natural intelligence working by being supported by such 5G network.

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