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Searching for New Physics in the Subatomic World – SciTechDaily

Particle physicists use lattice quantum chromodynamics and supercomputers to search for physics beyond the Standard Model.

Peer deeper into the heart of the atom than any microscope allows and scientists hypothesize that you will find a rich world of particles popping in and out of the vacuum, decaying into other particles, and adding to the weirdness of the visible world. These subatomic particles are governed by the quantum nature of the Universe and find tangible, physical form in experimental results.

Some subatomic particles were first discovered over a century ago with relatively simple experiments. More recently, however, the endeavor to understand these particles has spawned the largest, most ambitious and complex experiments in the world, including those at particle physics laboratories such as the European Organization for Nuclear Research (CERN) in Europe, Fermilab in Illinois, and the High Energy Accelerator Research Organization (KEK) in Japan.

These experiments have a mission to expand our understanding of the Universe, characterized most harmoniously in the Standard Model of particle physics; and to look beyond the Standard Model for as-yet-unknown physics.

This plot shows how the decay properties of a meson made from a heavy quark and a light quark change when the lattice spacing and heavy quark mass are varied on the calculation. Credit: A. Bazavov (Michigan State U.), C. Bernard (Washington U., St. Louis), N. Brown (Washington U., St. Louis), C. DeTar (Utah U.), A.X. El-Khadra (Illinois U., Urbana and Fermilab) et al.

The Standard Model explains so much of what we observe in elementary particle and nuclear physics, but it leaves many questions unanswered, said Steven Gottlieb, distinguished professor of Physics at Indiana University. We are trying to unravel the mystery of what lies beyond the Standard Model.

Ever since the beginning of the study of particle physics, experimental and theoretical approaches have complemented each other in the attempt to understand nature. In the past four to five decades, advanced computing has become an important part of both approaches. Great progress has been made in understanding the behavior of the zoo of subatomic particles, including bosons (especially the long sought and recently discovered Higgs boson), various flavors of quarks, gluons, muons, neutrinos and many states made from combinations of quarks or anti-quarks bound together.

Quantum field theory is the theoretical framework from which the Standard Model of particle physics is constructed. It combines classical field theory, special relativity and quantum mechanics, developed with contributions from Einstein, Dirac, Fermi, Feynman, and others. Within the Standard Model, quantum chromodynamics, or QCD, is the theory of the strong interaction between quarks and gluons, the fundamental particles that make up some of the larger composite particles such as the proton, neutron and pion.

Carleton DeTar and Steven Gottlieb are two of the leading contemporary scholars of QCD research and practitioners of an approach known as lattice QCD. Lattice QCD represents continuous space as a discrete set of spacetime points (called the lattice). It uses supercomputers to study the interactions of quarks, and importantly, to determine more precisely several parameters of the Standard Model, thereby reducing the uncertainties in its predictions. Its a slow and resource-intensive approach, but it has proven to have wide applicability, giving insight into parts of the theory inaccessible by other means, in particular the explicit forces acting between quarks and antiquarks.

A plot of the Unitarity Triangle, a good test of the Standard Model, showing constraints on the , plane. The shaded areas have 95% CL, a statistical method for setting upper limits on model parameters. Credit: A. Ceccucci (CERN), Z. Ligeti (LBNL) and Y. Sakai (KEK)

DeTar and Gottlieb are part of the MIMD Lattice Computation (MILC) Collaboration and work very closely with the Fermilab Lattice Collaboration on the vast majority of their work. They also work with the High Precision QCD (HPQCD) Collaboration for the study of the muon anomalous magnetic moment. As part of these efforts, they use the fastest supercomputers in the world.

Since 2019, they have used Frontera at the Texas Advanced Computing Center (TACC) the fastest academic supercomputer in the world and the 9th fastest overall to propel their work. They are among the largest users of that resource, which is funded by the National Science Foundation. The team also uses Summit at the Oak Ridge National Laboratory (the #2 fastest supercomputer in the world); Cori at the National Energy Research Scientific Computing Center (#20), and Stampede2 (#25) at TACC, for the lattice calculations.

The efforts of the lattice QCD community over decades have brought greater accuracy to particle predictions through a combination of faster computers and improved algorithms and methodologies.

We can do calculations and make predictions with high precision for how strong interactions work, said DeTar, professor of Physics and Astronomy at the University of Utah. When I started as a graduate student in the late 1960s, some of our best estimates were within 20 percent of experimental results. Now we can get answers with sub-percent accuracy.

Frontera was the fifth most powerful supercomputer in the world and fastest academic supercomputer, according to the November 2019 rankings of the Top500 organization. Frontera is located at the Texas Advanced Computing Center and supported by National Science Foundation. Credit: TACC

In particle physics, physical experiment and theory travel in tandem, informing each other, but sometimes producing different results. These differences suggest areas of further exploration or improvement.

There are some tensions in these tests, said Gottlieb, distinguished professor of Physics at Indiana University. The tensions are not large enough to say that there is a problem here the usual requirement is at least five standard deviations. But it means either you make the theory and experiment more precise and find that the agreement is better; or you do it and you find out, Wait a minute, what was the three sigma tension is now a five standard deviation tension, and maybe we really have evidence for new physics.'

DeTar calls these small discrepancies between theory and experiment tantalizing. They might be telling us something.

Over the last several years, DeTar, Gottlieb and their collaborators have followed the paths of quarks and antiquarks with ever-greater resolution as they move through a background cloud of gluons and virtual quark-antiquark pairs, as prescribed precisely by QCD. The results of the calculation are used to determine physically meaningful quantities such as particle masses and decays.

One of the current state-of-the-art approaches that is applied by the researchers uses the so-called highly improved staggered quark (HISQ) formalism to simulate interactions of quarks with gluons. On Frontera, DeTar and Gottlieb are currently simulating at a lattice spacing of 0.06 femtometers (10-15 meters), but they are quickly approaching their ultimate goal of 0.03 femtometers, a distance where the lattice spacing is smaller than the wavelength of the heaviest quark, consequently removing a significant source of uncertainty from these calculations.

Each doubling of resolution, however, requires about two orders of magnitude more computing power, putting a 0.03 femtometers lattice spacing firmly in the quickly-approaching exascale regime.

The costs of calculations keeps rising as you make the lattice spacing smaller, DeTar said. For smaller lattice spacing, were thinking of future Department of Energy machines and the Leadership Class Computing Facility [TACCs future system in planning]. But we can make do with extrapolations now.

Among the phenomena that DeTar and Gottlieb are tackling is the anomalous magnetic moment of the muon (essentially a heavy electron) which, in quantum field theory, arises from a weak cloud of elementary particles that surrounds the muon. The same sort of cloud affects particle decays. Theorists believe yet-undiscovered elementary particles could potentially be in that cloud.

A large international collaboration called the Muon g-2 Theory Initiative recently reviewed the present status of the Standard Model calculation of the muons anomalous magnetic moment. Their review appeared in Physics Reports in December 2020. DeTar, Gottlieb and several of their Fermilab Lattice, HPQCD and MILC collaborators are among the coauthors. They find a 3.7 standard deviation difference between experiment and theory.

While some parts of the theoretical contributions can be calculated with extreme accuracy, the hadronic contributions (the class of subatomic particles that are composed of two or three quarks and participate in strong interactions) are the most difficult to calculate and are responsible for almost all of the theoretical uncertainty. Lattice QCD is one of two ways to calculate these contributions.

The experimental uncertainty will soon be reduced by up to a factor of four by the new experiment currently running at Fermilab, and also by the future J-PARC experiment, they wrote. This and the prospects to further reduce the theoretical uncertainty in the near future make this quantity one of the most promising places to look for evidence of new physics.

Gottlieb, DeTar and collaborators have calculated the hadronic contribution to the anomalous magnetic moment with a precision of 2.2 percent. This give us confidence that our short-term goal of achieving a precision of 1 percent on the hadronic contribution to the muon anomalous magnetic moment is now a realistic one, Gottlieb said. The hope to achieve a precision of 0.5 percent a few years later.

Other tantalizing hints of new physics involve measurements of the decay of B mesons. There, various experimental methods arrive at different results. The decay properties and mixings of the D and B mesons are critical to a more accurate determination of several of the least well-known parameters of the Standard Model, Gottlieb said. Our work is improving the determinations of the masses of the up, down, strange, charm and bottom quarks and how they mix under weak decays. The mixing is described by the so-called CKM mixing matrix for which Kobayashi and Maskawa won the 2008 Nobel Prize in Physics.

The answers DeTar and Gottlieb seek are the most fundamental in science: What is matter made of? And where did it come from?

The Universe is very connected in many ways, said DeTar. We want to understand how the Universe began. The current understanding is that it began with the Big Bang. And the processes that were important in the earliest instance of the Universe involve the same interactions that were working with here. So, the mysteries were trying to solve in the microcosm may very well provide answers to the mysteries on the cosmological scale as well.

Reference: The anomalous magnetic moment of the muon in the Standard Model by T. Aoyama, N. Asmussen, M. Benayoun, J. Bijnens, T. Blum, M. Bruno, I. Caprini, C. M. Carloni Calame, M. C, G. Colangelo, F. Curciarello, H. Czyz, I. Danilkin, M. Davier, C. T. H. Davies, M. Della Morte, S. I. Eidelman, A. X. El-Khadra, A. Grardin, D. Giusti, M. Golterman, StevenGottlieb, V. Glpers, F. Hagelstein, M. Hayakawa, G. Herdoza, D. W. Hertzog, A. Hoecker, M. Hoferichter, B.-L. Hoid, R. J. Hudspith, F. Ignatov, T. Izubuchi, F. Jegerlehner, L. Jin, A. Keshavarzi, T. Kinoshita, B. Kubis, A. Kupich, A. Kupsc, L. Laub, C. Lehner, L. Lellouch, I. Logashenko, B. Malaescu, K. Maltman, M. K. Marinkovic, P. Masjuan, A. S. Meyer, H. B. Meyer, T. Mibe, K. Miura, S. E. Mller, M. Nio, D. Nomura, A. Nyffeler, V. Pascalutsa, M. Passera, E. Perez del Rio, S. Peris, A. Portelli, M. Procura, C. F. Redmer, B. L. Roberts, P. Snchez-Puertas, S. Serednyakov, B. Shwartz, S. Simula, D. Stckinger, H. Stckinger-Kim, P. Stoffer, T. Teubner, R. Van de Water, M. Vanderhaeghen, G. Venanzoni, G. von Hippel, H. Wittig, Z. Zhang, M. N. Achasov, A. Bashir, N. Cardoso, B. Chakraborty, E.-H. Chao, J. Charles, A. Crivellin, O. Deineka, A. Denig, C. DeTar, C. A. Dominguez, A. E. Dorokhov, V. P. Druzhinin, G. Eichmann, M. Fael, C. S. Fischer, E. Gmiz, Z. Gelzer, J. R. Green, S. Guellati-Khelifa, D. Hatton, N. Hermansson-Truedsson, S. Holz, B. Hrz, M. Knecht, J. Koponen, A. S. Kronfeld, J. Laiho, S. Leupold, P. B. Mackenzie, W. J. Marciano, C. McNeile, D. Mohler, J. Monnard, E. T. Neil, A. V. Nesterenko, K. Ottnad, V. Pauk, A. E. Radzhabov, E. de Rafael, K. Raya, A. Risch, A. Rodrguez-Snchez, P. Roig, T. San Jos, E. P. Solodov, R. Sugar, K. Yu. Todyshev, A. Vainshtein, A. Vaquero Avils-Casco, E. Weil, J. Wilhelm, R. Williams and A. S. Zhevlakov, 14 August 2020, .DOI: 10.1016/j.physrep.2020.07.006

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Searching for New Physics in the Subatomic World - SciTechDaily

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Herms collaborates with artists on Watches and Wonders 2021 scenography – Wallpaper*

Herms collaborates with artists on Watches and Wonders 2021 scenography

Herms has worked with Clment Vieille and Pierre Pauze on the backdrop to its newest watch release, the H08, unveiled as part of the Watches and Wonders fair

Herms marksthe first day of Watches and Wonders 2021 by unveiling the backdrop from which it will release its newest watch, the H08. The scenography is the result of a collaboration with two artists, Clment Vieille and Pierre Pauze.

The physical exhibition, in Genevas Btiment des Forces Motrices, promises to be one of the highlights of this years fully digital show. Embodying a digital vision, it is composed of a set of videos and sculptures which explore both time and natural cycles.

At the centre of the staging is Herms new watch release, the H08. The watchhas been interpreted by the two artists both from Le Fresnoypostgraduate art and audiovisual research centre who have broken it down and juxtaposed it against natural elements. Its patterns, once exposed, are explored on 16 screens. Pierre Pauze is passionate about quantum physics, which allows us to see beyond linear temporality. He explores cyclical time and uses natural cycles as the temporal structure of his kinetic art, says Laurent Dordet, CEO of La Montre Herms.

Clment Vieille places research and technique at the centre of his creative process, reducing a static structure to its lines of tension and compression. Vieille invites visitors into what appears to be an infinite cylinder, with two large mirrors on the floor endlessly reflecting the sculpture.

For Vieille, it was a balancing act between the technology thatdefines the design and the traditions of hand craftsmanship that characterise Herms. The watch itself was the initial inspiration but was then interpreted, piece by piece, to fill the whole of the large showcase. In the end, the watch becomes almost imperceptible, but the thousands of translucent sculptures that populate the showcase come from a 3D file of the watch I was given at the beginning of the project. It is omnipresent without one really noticing it.

Adds Pauze, It was as if it was being infused little by little with ideas of organic and mechanical fluidity. It was at this point that we suggested to Herms that we merge these energies and resources into two parallel projects. The watch is mostly integrated in fragments and through evocation. The idea was to move away from the usual aesthetic that puts the product first. I think that as a watch is worn, it is also experienced. The work does not replace the watch, and the watch does not replace the work. They thus maintain their respective strengths.

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This Is the Most Powerful Artificial Intelligence Tool in the World – Entrepreneur

April7, 20215 min read

Opinions expressed by Entrepreneur contributors are their own.

In June 2020, the Californian company OpenAI announcedGPT-2's upgrade to GPT-3 , a language model based on artificial intelligence and deep learning with cognitive capabilities. It is atechnology that has generated great expectationsand that has been presented as the most important and useful advance in AI in recent years.

OpenAI is a non-profit company founded by Elon Musk, co-founder and director of Tesla and SpaceX, which was born with the aim of researching and democratizing access to General Artificial Intelligence. Originally, it was a non-profit organization. However, in 2020, it becamea company andpartnered with Microsoft in order to achieve new advances, both in the field of language with GPT-3 models, and in the field of robotics and vision.

GPT-3 (Generative Pre-Training Transformer 3) is what is known as an autoregressive language model, which uses deep learning to produce texts that simulate human writing.

Unlike most artificial intelligence systems that are designed for a use case, this API (Application Programming Interface) provides a general-purpose "text input and output" interface, allowing users to test it. in practically any assignment in English. This tool is capable of, among other functions, generating a text on any subject that is proposed to it in the same way as a human would, programming (in HTML code) and generating ideas.

As Nerea Luis, an expertin artificial intelligence and engineer at Sngular, says, GPT-3 is living confirmation that the Natural Language Processing area is advancing more than ever by leaps and bounds."

Do you want to know how GPT-3 works? Now I explain it to you.

The user only has to start writing a paragraph, and the system itself takes care of completing the rest of the text in the most coherent way possible. Also, with GPT-3 you can generate conversations and the answers provided by the system will be based on the context of the previous questions and answers.

It should be noted that the tool generates text using algorithms that were previously trained, and that have already received all the data they need to carry out their task. On time, they have received around 570 GB of text information collected by crawling the Internet (a publicly available dataset known as CommonCrawl) along with other text selected by OpenAI, including text from Wikipedia .

GPT-3 has aroused a lot of interest because it is one of the first systems to show the possibilities of general artificial intelligence, because it completes with surprisingly reasonable results tasks that until now required a specially built system to solve that particular task. Furthermore, it does so from just a few examples, says Csar de Pablo, data scientist at BBVA Data & Analytics.

As for the possible applications that this tool may have, I mention the following:

GPT-3 will be able to generate text for websites , social media ads, scripts , etc. In this way, with a few simple guidelines of the needs you have, GPT-3 will transform it into a precise text. In addition, you can select the type of text you need, from the most generic to the most strategic and creative.

With GPT-3 you will be able to compose emails (among other functions) by simply giving it some guidelines of what you want to say and communicate. For example, through magicemail.io, a portal where you can test the tool (there is a waiting list of about 6000 users), you can see how it works. As a Google Chrome extension, Magicemail will be installed in our Gmail.

When an email arrives, we will simply have to click on the tool to receive a phrase of what they want to tell us in the email.

GPT-3 will develop the code just by telling it how we want our landing page or website to look. Once you give us the HTML code, we will only need a "copy and paste" to have an optimal result. The tool will significantly streamline web development processes.

With this model, chatbots will be much more accurate, with more accurate responses, generating in the user a value of more personalized and effective attention.

Furthermore, GPT-3 could have huge implications for the way software and applications are developed in the future.

A sample of how this technology works can be seen in the essay Are you still scared, human?,published by The Guardian that, as its editor comments, was made from the best fragments of eight articles generated with GPT-3 in order to capture the different styles and registers of artificial intelligence.

Another demo available online is "GPT-3: Build Me A Photo App,"which shows the creation of an application that looks and works similar to the Instagram application, using a plugin for the Figma software tool, which is widely used for application design.

Let us remember that currently the use that is given to the GPT-3 model is mainly limited to the research community. However, it is clear that GPT-3 in the near future may create everything that has a language structure, such as: answering questions, writing essays, summarizing texts, translating, taking notes and even creating code for computers.

Therefore, GPT-3 is positioned as an artificial intelligence tool with great potential for the future. And, surely, when it is open to the public, its reach will be much more surprising.

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This Is the Most Powerful Artificial Intelligence Tool in the World - Entrepreneur

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Johnson Controls and Pelion Partner on Artificial Intelligence / Internet of Things (AIoT) For Smart, Healthy, and Sustainable Buildings -…

Partnership accelerates innovation by removing the complexities of bringing artificial intelligence (AI) to a diversity of devices at the edge, enabling smarter buildings that evolve and adapt through Johnson Controls OpenBlue technology

Johnson Controls to leverage Pelions connected device platform for IoT device management services that simplify monitoring, maintaining, and improving the health, security, and performance of edge devices and workloads.

SAN JOSE, Calif.(BUSINESS WIRE)Today, Pelion, the Connected IoT Device service provider, and subsidiary of Arm, jointly announced a partnership with Johnson Controls (NYSE: JCI), the global leader for smart, healthy and sustainable buildings. This partnership will accelerate innovation in connectivity, security and intelligence at the edge for Johnson Controls OpenBlue technology.

This partnership combines Johnson Controls deep domain expertise in healthy buildings with Pelions device and edge management capabilities to usher in an era of truly smart, updateable facilities at cloud scale. said Mike Ellis, chief customer and digital officer for Johnson Controls. OpenBlues AI capabilities at the edge will consolidate diverse points of intelligence distributed across various floors, sites or even continents into insights and actions, creating an updateable building that can self-heal and evolve over its lifespan.

This innovation mirrors the automotive sector, where software, multiple sensors and AI-trained models have transformed the industry by enabling autonomous driving and software updates that blend data to continually improve vehicle capabilities and experience. Johnson Controls is applying the concept to the built environment. They will leverage Pelions flexible device management capabilities to unite diverse device types and application layers to feed AI models that respond to dynamic workloads.

Johnson Controls has the strategic foresight to rely on a partner to streamline the complexity of IoT device management security and secure firmware updates over the air, said Hima Mukkamala, CEO of Pelion. Pelions connected device platform will standardize the onboarding process for all systems, including the edge and endpoint devices that run on them, plus offer world-class public key infrastructure for secure and simple integration with third-parties.

This secure, open and flexible approach to device management will allow OpenBlue to run any device and hardware configuration, from hardware gateways to constrained temperature sensors.

In order to provide sustainable, low cost and low power intelligent processing at the edge, the partnership will utilize proven energy-efficient processors from Pelions parent company, Arm, which are a key part of Johnson Controls distributed hardware deployment.

For more on the partnership, Pelion CEO Hima Mukkamala has shared his thoughts in a blog post on the Johnson Controls website.

About Johnson Controls:

At Johnson Controls (NYSE:JCI), we transform the environments where people live, work, learn and play. As the global leader in smart, healthy and sustainable buildings, our mission is to reimagine the performance of buildings to serve people, places and the planet. With a history of more than 135 years of innovation, Johnson Controls delivers the blueprint of the future for industries such as healthcare, schools, data centers, airports, stadiums, manufacturing and beyond through its comprehensive digital offering, OpenBlue. With a global team of 100,000 experts in more than 150 countries, Johnson Controls offers the worlds largest portfolio of building technology, software and service solutions with some of the most trusted names in the industry. For more information, visit http://www.johnsoncontrols.com or follow us @johnsoncontrols on Twitter.

http://www.johnsoncontrols.com

About Pelion:

Pelion was originally founded as an incubation unit within Arm, the worlds leading designer of key technologies at the heart of computing. Now a wholly-owned subsidiary of Arm, Pelion is forging its own path in the IoT revolution, building on a solid foundation of device expertise and a 500-enterprise strong customer base. With a unique combination of global IoT connectivity and device management from a single vendor, Pelion breaks down barriers to IoT adoption for anyone looking to revolutionize their industry.

http://www.pelion.com

About Arm:

Arm technology is at the heart of a computing and data revolution that is transforming the way people live and businesses operate. Our energy-efficient processor designs and software platforms have enabled advanced computing in more than 180 billion chips and our technologies securely power products from the sensor to the smartphone and the supercomputer. Together with 1,000+ technology partners we are at the forefront of designing, securing and managing all areas of AI-enhanced connected compute from the chip to the cloud.

http://www.arm.com

Contacts

Johnson Controls Contacts:Investors:Antonella Franzen

Direct: 609.720.4665

Email: antonella.franzen@jci.com

Ryan Edelman

Direct: 609.720.4545

Email: ryan.edelman@jci.com

Media:Chaz Bickers

Direct: 224.307.0655

Email: charles.norman.bickers@jci.com

Michael Isaac

Direct: +41.52.6330374

Email: michael.isaac@jci.com

Pelion Analyst And Media Contacts:PelionPress@archetype.co

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Johnson Controls and Pelion Partner on Artificial Intelligence / Internet of Things (AIoT) For Smart, Healthy, and Sustainable Buildings -...

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Three keys to working effectively on Artificial Intelligence projects – BBVA

On many occasions, the greatest impediments to creating Artificial Intelligence solutions do not lie in the capacity of highly qualified teams, but in establishing an effective way of working between the different professional profiles involved in the life cycle of analytical models. This is one of the main tasks we are currently tackling at BBVA AI Factory. It is a task guided by three concepts: simplify, accelerate and reuse.

My first direct contact with the AI Factory was in April 2020, in the middle of lockdown. I found myself with a team of data scientists who were extremely competent in creating AI models, but who needed to continue to push for common working guidelines in order to deal with the complexity both organisational and technical that exists in the Engineering domain. At the end of the day, models and data engines have to be integrated into the various channels of the bank to be made available to our clients. This makes it essential to work together as one team. The best models are those that reach the end user.

One of the main chapters we are starting to work on is precisely to simplify the collaboration model between the worlds of data science and engineering, thus reducing organisational complexity and allowing teams to gain autonomy. It is important to understand the complete development cycle (data preparation, engine development and integration) and the role of each team during each phase, trying to eliminate blockages which are often caused by incorrect management of the dependencies between the different work groups.

Anticipating dependencies allows us to accelerate the delivery of models and data engines and also to parallelise the work of all the teams. Without a doubt, being able to gather feedback on how our models behave in the quickest possible time is a fundamental aspect for us. Our aspiration is to reduce the total time we spend on building analytical models, from the definition phase of the solution for a specific business need, to its implementation in production. In this sense, it is key to measure these times in detail and use this metric as a lever for the continuous improvement of the entire development cycle. In short, it is a matter of reducing downtime, being more efficient and responding better to the expectations of the teams.

The third major challenge in order to make Artificial Intelligence work more effectively is to be able to reuse developments as much as possible. We start from a way of working in which data scientists and Machine Learning engineers work on specific projects in which they have a partial vision of the problem to be solved. We have to integrate all these visions and build global data products that can be reused in the different areas and countries in which BBVA operates. This way, when we design a new data-based product, it can be exported and adapted much more easily. At present, synergies are detected, but sometimes teams face similar challenges without taking into account the previous work and experience of other areas.

With these ideas in mind, as COO (Chief Operating Officer) I join this great AI Factory team, recently set up as part of the BBVA Group, acting as a bridge between the worlds of Data and Engineering. Furthermore, I am fortunate to be doing this alongside Francisco Maturana (Company CEO) and Ricardo Oliver (head of Data Engineering at BBVA), from whom I receive key support and with whom I am fully in tune in the implementation of these working guidelines. In recent years I have worked within the Architecture & Global Deployment team after spending most of my career at BBVA in the field of technical and banking architectures, both in Spain and in different countries in the Americas (Mexico, Peru, Colombia, Venezuela and the United States). Right now I am looking forward to meeting my colleagues from the AI Factory in person, ( health situation permitting) and to thank them for the fantastic welcome I have received.

Before ending this short article, I think it is most appropriate to mention the reason why we want to continue advancing the lines of work mentioned above. Ultimately, our purpose is none other than to squeeze all the potential offered by Artificial Intelligence, whether it be in decision-making, process optimisation or in the creation of products that offer added value to our clients. That is why we are working on aspects such as interpretability and fairness in analytical models. We are convinced that AI will bring significant benefits to society in general and to our clients in particular, supporting them in making the best financial decisions.

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Banking Regulatory Agencies Seek Information on Financial Institutions Use of Artificial Intelligence – JD Supra

Five federal banking regulatory agencies are gathering information and comments on financial institutions use of artificial intelligence (AI), including machine learning. On March 29, the Federal Reserve Board, the Consumer Financial Protection Bureau, the Federal Deposit Insurance Corporation, the National Credit Union Administration, and the Office of the Comptroller of the Currency issued a request for information (RFI) seeking information on the following topics:

The RFI notes that financial institutions have been and are exploring AI-based applications for a variety of purposes. For example, financial institutions use chatbots and virtual assistants to mimic live employees and automate routine customer interactions. AI also can inform credit decisions by analyzing traditional data (i.e., data typically found in a consumers credit files) and alternative data. Financial institutions may use cybersecurity applications to detect threats and malicious activity, to conduct real-time investigations of potential attacks, and to block ransomware and other attacks.

Not surprisingly, regulators are paying close attention to the presence of AI in the financial services industry, as the industrys use of AI shows no signs of slowing down. In October 2020, Mastercard introduced an AI-powered suite of tools that allows banks to assess cyber risk and prevent potential breaches. In February of this year, Google Cloud and European-based BBVA announced a strategic partnership that includes an agreement to collaborate in the development of new AI and machine learning models to prevent cyberattacks. Jumio, a California-based Junio provider of AI-powered identify verification and know your customer solutions, closed a $150 million round of funding just last month. A few days later, California-based Feedzia raised $200 million for its AI-based ID verification and anti-money laundering platform.

Although the potential benefits of AI are apparent, the RFI cautions that financial institutions should implement processes for identifying and managing potential risks, especially those that could affect an institutions safety and soundness. Such risks include potential operational vulnerabilities, such as internal process or control breakdowns, cyber threats, information technology lapses, risks associated with the use of third parties, and model risk. The RFI also warns of certain consumer protection risks, such as unlawful discrimination, UDAAP and UDAP violations, and privacy concerns.

The RFIs broad inquiry into financial institutions use of AI may give rise to some trepidation by financial institutions, but they should consider using the RFI as an opportunity to educate regulators about the benefits of AI and to seek clarification on how their use of AI could raise compliance concerns when using AI in their respective businesses.

Comments are due 60 days after publication in the Federal Register.

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Banking Regulatory Agencies Seek Information on Financial Institutions Use of Artificial Intelligence - JD Supra

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Alight pairs data and artificial intelligence to transform the HR experience and drive business outcomes – Yahoo Finance

Alight Worklife helps deliver superior employee experiences that become catalysts for enterprise growth

Alight Solutions, a leading cloud-based provider of integrated digital human capital and business solutions, today announced Alight Worklife, an enterprise technology platform that drives measurable value through highly personalized interactions with employees.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20210408005235/en/

Alight Worklife brings Alights industry-leading technology together into a single platform with a focus on shaping employee experiences and driving better outcomes for employers and their people. With Alight Worklife, employees can easily access and engage with their HR and benefits applications anytime, anywhere. For their part, employers can use analytics and AI to provide employees with targeted support that drives engagement, boosts productivity and improves retention across the enterprise.

Greater value for employees

Alight Worklifes suite of web-based tools is integrated with the mobile app to deliver a seamless digital experience for employees. Alight Worklife uses a robust data engine and AI to send personalized HR and benefits recommendations, based on peoples life situations and engagement, to their preferred channel or device. This allows employees to make better decisions and maximize the employer benefits provided to them.

"Employers have a unique opportunity to help their people who face a constant barrage of information in their digitally-driven lives, but have trouble understanding whats important and how to act on it," said Colin Brennan, chief product strategy & services officer at Alight. "Alight Worklife aggregates, surfaces and personalizes data in a way that engages employees at their point of need and helps them make smarter decisions around their health, wealth and wellbeing."

Transformative results for organizations

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Alight Worklife equips organizations with data-driven insights on how employees are engaging with HR and their benefits that employers can use to improve employee experiences and tie them to transformative results. Employers can benchmark against industry metrics based on human capital and business data managed by Alight for more than 4,300 organizations and 30 million employees and their family members.

"Organizations continue to rapidly invest in transformation, but many arent seeing meaningful improvement in employee experiences, so its becoming increasingly clear that much of that investment is wasted," said Greg Goff, chief product & technology officer at Alight. "For employers striving for greater productivity and increased efficiency, Alight Worklife gives them unique insights into how employee decisions and behaviors are impacting top- and bottom-line performance."

Scalable solutions for enterprise growth

Alight Worklife is the platform that powers Alights three core cloud-based solutions, which are designed to scale and meet the specific needs of organizations and their people:

Health Cloud Alight administers benefits, navigates the healthcare system, and provides personalized support to help employees make smarter, cost-effective health decisions for themselves and their families. By having a healthier and better-informed workforce, organizations can reduce their healthcare spend, control downstream costs and improve overall benefits program satisfaction.

Wealth Cloud Alights intelligent, highly personalized tools help employees navigate financial uncertainty, manage day-to-day financial obligations, and save for retirement. By integrating the full financial picture of employees lives, from everyday budgeting to managing life events, organizations can reduce employees financial stress and build and sustain a productive workforce.

Payroll Cloud Alights modernized payroll systems ensure employees are paid accurately, on-time, and on their channel of choice, including digital wallets. Organizations can also analyze global pay data more thoroughly with AI and robotic process automation and meet all compliance requirements.

For more information on Alight Worklife is available at alight.com.

About Alight Solutions

With an unwavering belief that a companys success starts with its people, Alight Solutions is a leading cloud-based provider of integrated digital human capital and business solutions. Leveraging proprietary AI and data analytics, Alight optimizes business process as a service (BPaaS) to deliver superior outcomes for employees and employers across a comprehensive portfolio of services. Alight allows employees to enrich their health, wealth and work while enabling global organizations to achieve a high-performance culture. Alights 15,000 dedicated colleagues serve more than 30 million employees and family members. Learn how Alight helps organizations of all sizes, including over 70% of the Fortune 100 at alight.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20210408005235/en/

Contacts

Landis CullenLandis.Cullen@Alight.com

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Alight pairs data and artificial intelligence to transform the HR experience and drive business outcomes - Yahoo Finance

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CDW Tech Talk: Finding the Humanity in Artificial Intelligence and Big Data – BizTech Magazine

How to Steer Your Organization Toward Being More Data-Driven

Many businesses looking to build data programs may lack the operational management needed to implement a data-driven vision, and their technology leaders may be left wondering how to make it happen.

Clingerman offered this advice: Look to see whats happening within your industry verticals and competition. Where are others taking advantage of data?

He cited Uber as a prime example of a small startup that was able to harness the data collected out of the application it built. Upon discovering that many customers were using Uber as transportation to and from restaurants, the data the company collected enabled it to create a whole new line of business with Uber Eats.

The vision and cultural aspects of an organization are what allow a business to take this data and use it to realize the promise of AI.

Clingerman mentioned several examples of how AI has recently been harnessed to benefit society. In the transportation sector, autonomous cars have helped to enable safer transportation. In agriculture, sensors placed on farm equipment have been used to maximize crop yields. AI has been used to power smart cities, ensuring safer, more secure cities and more reliable public transportation.

However, with all the data organizations are contending with, Clingerman said its absolutely critical for organizations to consider ethics when deciding how to harness and use that data.

How do we use this data only for good? How do we ensure that its safe and secure? How do we anonymize the information as much as possible? he asked. All of our decisions are focused on how organizations leverage technology to drive human progress forward. Its not about the technology. What are we doing to better our society?

WATCH THE WEBCAST: Unlock the Insider-exclusive video to learn more about the intersection of technology and social responsibility.

Kristin Malek, director of business diversity at CDW, also joined the session to speak about the ways in which procurement and supply chain management can provide opportunities for businesses looking to prioritize positive societal and economic impacts in their decision-making.

She quoted a January 2020 Deloitte study, which notes that The term ethical technology refers to an overarching set of values that is not limited to or focused on any one technology, instead addressing the organizations approach to its use of technologies as a whole and the ways in which they are deployed to drive business strategy and operations. Companies should consider proactively evaluating how they can use technology in ways that are aligned with their fundamental purpose and core values.

There is a real-time demand in our country and beyond for equity in the workplace, in the workforce and in our new digital supply chain, Malek added.

She emphasized that in 2021, business diversity and supply chain diversity arent just nice to have. Its not charity, its not sprinkling kindness throughout. It is an absolute revenue enabler.

Were all looking for a promise of progress, she said. Business diversity is about realizing that progress through decision-making that factors in social responsibility and supply chain choices that employ impactful sourcing and intentional procurement, because instead of tracking dollars spent, we need to be tracking the lives that were enriching.

So, whats on the table? Whats the business case? she asked, noting the many competing strategies all organizations are focused on right now. Its meaningful job creation, its revenue enablement, its greater market share and its done with sustainable and ethical procurement.

FollowBizTechs full coverage of the CDW Tech Talk serieshere. Insiders can register for the event serieshere.

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CDW Tech Talk: Finding the Humanity in Artificial Intelligence and Big Data - BizTech Magazine

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Policymaking and artificial intelligence: A conversation with John R. Allen and Darrell M. West – Brookings Institution

Until recently, artificial intelligence sounded like something out of science fiction. But the technology of artificial intelligence (AI) is becoming increasingly common, from self-driving cars to e-commerce algorithms that seem to know what you want to buy before you do. Throughout the economy and many aspects of daily life, artificial intelligence has become the transformative technology of our time.

On April 21, 2021, Sanjay Patnaik, director of the Center on Regulation and Markets (CRM) at Brookings will sit down with John R. Allen, president of the Brookings Institution, and Darrell M. West, vice president and director of Governance Studies at Brookings, for a fireside chat on their book, Turning Point: Policymaking in the Era of Artificial Intelligence. Drawing on findings and recommendations from Turning Point, they will explore the risks and opportunities of artificial intelligence and discuss a policy blueprint for how to gain the benefits of artificial intelligence while reducing its potential disadvantages. This event will be part of CRMs Reimagining Modern-day Markets and Regulations series, which focuses on analyzing rapidly changing modern-day markets and on how to regulate them most effectively.

Viewers can submit questions for speakers by emailing events@brookings.edu or via Twitter using #AIGovernance.

Turning Point: Policymaking in the Era of Artificial Intelligence is available to order in print and e-book on the Brookings Press page.

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Policymaking and artificial intelligence: A conversation with John R. Allen and Darrell M. West - Brookings Institution

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Artificial intelligence can bring the Human back to HR – The Financial Express

This proliferation of technology has stoked the fear of cold and calculated robots replacing human interaction.

By Sukhjit Pasricha,

Artificial Intelligence and machine learning have automated processes, streamlined operations and have also started making intelligent decisions. This proliferation of technology has stoked the fear of cold and calculated robots replacing human interaction.

Despite these concerns, a recent study has found that 93% of people are ready to take orders from a robot and more than a third of employees believe that AI will enable better customer and employee experiences. Even then, only 6% of HR teams are actively deploying AI and machine learning solutions. This chasm reveals the missed opportunity for AI to help HR meet evolving employee expectations for a personalised, relevant work environment.

When it comes to the use of AI, most HR professionals have reservations that AI will make this human-centric function less human. What if it can be proved that by embracing AI you could make HR more humane. It sounds ironic, however, if AI implementation is done in synchronisation with other HCM solutions, it can enable organisations to hire better, onboard smarter and retain people longer.

Recruiting Experience like never before

Recruitment is one of the scariest parts of HR. Incessant pressure from teams to find the perfect fit and endless hours of search often result in dead ends or unsuitable hires. In such a situation, AI-backed tools can help HR to take a more strategic approach to recruiting. AI, being fed with data, can identify talent with qualities that match those of existing successful employees and proactively invite them to apply. This makes the entire hiring process more efficient and the only resumes that HR and business teams will be sifting through are those of truly qualified candidates. And when the process eventually results in an offer, companies will have data-backed justification for the hiring decision.

Seamless Onboarding Process

The importance of a good onboarding process can be gauged from the fact that 17% of new hires resign within three months and 15% of those cited the lack of effective onboarding as the reason for their resignation. Change of employment is one of the most crucial decisions that one makes, and an unorganised and a difficult onboarding process will fail to reassure employees of their decision to join the organisation. Despite the realisation of the importance of the role that a good onboarding experience plays in employee engagement/ affinity, productivity and retention, however, a surprising number of businesses still lack an intuitive, formalised process.

Digital assistants also play a significant role in humanising the onboarding experience. The onboarding process can vary greatly from employee to employee, so instead of relying on an HR representative for help with commonly asked HR questions, new hires can now chat with a digital concierge to get quick access and answers.

Minimise Employee Turnover

An organisation is caught unaware when suddenly a great employee leaves because of lack of job satisfaction and motivation. Had the HR team been aware of the employees thought process, appropriate steps could have been taken to tailor the employees experience according to his or her expectations or needs.

AI can be an effective tool in HRs hands to provide them with data-backed insights on motivating factors for an employee. Thus, HR can play a crucial role in retaining employees by creating a personalised experience that meets both the employee and organisations goals. Furthermore, AI can help HR to analyse traits and reasons for the resignation. This way HR can raise a flag when similar behaviour patterns emerge and can take preventive measures proactively.

A world of Endless Possibilities

In the talent economy, the future of any organisation will depend on its ability to attract and retain brilliant employees. Embracing the possibilities offered by artificial intelligence in HR, can transition an organisations environment from one facing high turnover to one that embraces a truly humane experience.

(The author is President & Group Chief Human Resource Officer, Kotak Mahindra Bank and Shaakun Khanna, Head HCM Applications, Oracle Asia Pacific. Views expressed are personal and do not reflect the official position or policy of the Financial Express Online.)

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Artificial intelligence can bring the Human back to HR - The Financial Express

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