Page 1,851«..1020..1,8501,8511,8521,853..1,8601,870..»

The Power of Internships: Jennifer Vera ’23 Builds Resume-Ready Skills with U.S. Marshals, FEMA, and More | John Jay College of Criminal Justice -…

Jennifer Vera 23 knew she wanted a career in law enforcement, a goal fueled by a teacher's dismissive comment. I mentioned that I wanted to go into federal law enforcement to a substitute teacher and she told me that I looked too vulnerable for the job. She said it was an unrealistic goal, says Vera, a forensic psychology and anthropology major. When I came to John Jay, I used her words as a form of motivation. To prepare, the Brooklyn native landed internships with the U.S. Marshals Service, the Federal Emergency Management Agency [FEMA], the New York City Department of Investigation [NYC DOI] and private investigators with support from LEAP[Linking Experience, Academics, and Practice] and the alumni mentoring program.

John Jayteaches justice core values and offers amazing opportunities thanks to the many alumni, faculty, and staff that have worked in the criminal justice field.Jennifer Vera 23

Why was John Jay the right college for you?John Jay was my first choice for three reasons: First, it teaches justice core values and offers amazing opportunities thanks to the many alumni, faculty, and staff that have worked in the criminal justice field. Second, its a Hispanic-Serving Institution, which really means a lot to me because I grew up speaking Spanish, surrounded by Colombian and Ecuadorian culture. And third, I saw John Jays beautiful architecture on television shows, and that made me want to come here even more.

How has John Jay helped support your success?My LEAP advisor, Cristina Di Meo, encouraged me to apply to the alumni mentoring program, which connected me with my mentor Cynthia Cavalie-Gonzalez 02, a private investigator. Cynthia has taught me all about the private investigative field and she helped me become a student mentee for theCalifornia Association of Licensed Investigators[CALI]. Because of LEAP, I know what my interests are, the steps I need to take to reach my goals, and what it takes to be a leader.

Because of LEAP, I know what my interests are, the steps I need to take to reach my goals, and what it takes to be a leader.Jennifer Vera 23

What have your internship experiences been like so far?Last fall, with the help of CALI, I interned with Nardello & Co., a private investigative firm. There, I conducted open-source research, used data mining software, and created proposals. This spring, I interned with theU.S. Marshals Servicewhere I worked with different divisions, including warrants, civil, protective intelligence, criminal, and asset forfeiture. There were a lot of amazing hands-on experiences, like intrusion simulations and shooting range activities. I also really enjoyed their fitness training tests. It wasnt easy the first time, but I was proud of myself for improving my fitness performance.

What internships are you looking forward to this year?Im excited to work with FEMA and the New York City Department of Investigation. At FEMA, Ill be interning in the national preparedness division. Some of my responsibilities will include providing research, organizing webinars, and developing bulletin articles. At the New York City Department of Investigation, theyve asked that I assist in conducting interviews, developing investigative strategies, and identifying relevant records. Its rewarding to know that at FEMA, in some small way, Ill help protect people from hazards and disasters; and at the Department of Investigation, Ill help prevent fraud and corruption.

I want to demonstrate to Latina women that we can work in these traditionally male-dominated fields, and excel in them.Jennifer Vera 23

Where do you see yourself in 10 years?I hope to get my masters degree in international crime and justice and become a criminal investigator. My ultimate goal is to bring peace and justice into victims lives. I also want to demonstrate to Latina women that we can work in these traditionally male-dominated fields, and excel in them. One day I see myself speaking in front of a group of young Latina women and inspiring them to follow in my footsteps.

Continued here:

The Power of Internships: Jennifer Vera '23 Builds Resume-Ready Skills with U.S. Marshals, FEMA, and More | John Jay College of Criminal Justice -...

Read More..

Servify raises Rs 520 crore in new round; aims for IPO in two years – Business Standard

Servify, a company that manages lifecycle of devices for several smartphone vendors in many markets, on Wednesday said it has raised USD 65 million (around Rs 520 crore) in a round led by Singularity Growth Opportunity Fund.

The startup, which serves global brands like Samsung and Apple, has raised the money at a valuation which is just under USD 1 billion, its founder Sreevathsa Prabhakar told PTI, adding that it would have achieved the 'unicorn' status after this round itself, if not for a few challenging conditions set by investors.

It has consciously raised money from domestic investors in this round because it aims to go public through an Initial Public Offering (IPO) in the next 18-24 months, he said.

Investors in the new round include family offices like that of Pidilite, and also existing investors like Iron Pillar, BEENEXT, Blume Ventures, and DMI Sparkle Fund, he said, adding there is a possibility of it raising another USD 5-7 million in the next month to close the round at USD 70 million.

Prabhakar said the six-year-old company is currently delivering an annual revenue run rate of over USD 130 million and will turn profitable in the next two months.

Hence, there was no need of capital per se, but the round got done with the ultimate aim of listing in mind, he said, adding the listing will happen once it is profitable for over 15 months.

Right now, 60 per cent of its revenue comes from domestic market and the rest from overseas market, he said.

In the next two years, international revenues will be 90 per cent of the pie as it takes the network to more countries and deepens its reach in the 40 countries that it operates in.

The company gets annuity income either from end-consumers or equipment manufacturers like Samsung and Apple to service a product during its lifecycle, and depends a lot on data mining and tech tools.

Prabhakar said it has data on 750 million customers and called it one of its biggest assets which is monetised, as the company uses it to better its understanding of usage patterns, maintenance events etc to underwrite better and widen its margins.

It had obligations to serve 4.8 million consumers as of end-FY22 and sees the same rising to over 10 million by end of the current fiscal, Prabhakar said, adding that it is doing 3.4 million transactions a month.

"Product protection is no longer an afterthought; in fact, it is rapidly taking centre stage for both OEMs and consumers. We, therefore, see Servify steadily moving towards global leadership in this massive addressable market of over USD 100 billion," Apurva Patel, a managing director at Singularity, said.

(Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)

See the original post here:

Servify raises Rs 520 crore in new round; aims for IPO in two years - Business Standard

Read More..

Using AI to Match Patients with Clinical Trials for Proactive Treatment – HIT Consultant

Lucas Glass,VicePresidentoftheAnalyticsCenterofExcellence, IQVIA

We are entering a new era of patient treatment options thanks to cutting-edge technologies that are changing the way life science companies approach and execute pharmaceutical research. One of the more significant solutions that support the faster and more efficient development of new pharmaceutical products such as the COVID-19 vaccine, which was developed faster than any other vaccine in history is artificial intelligence (AI)-driven data analysis. Thanks to modern life science technology solutions that employ AI for data analysis, new treatments for various illnesses can be made safer, faster and more focused on specific conditions.

21st Century Patient Treatment for Rare Illnesses

It can be difficult to develop treatments for patients dealing with rare illnesses, as it is often difficult to find enough patients to conduct thorough clinical research. Further, because the condition is rare, there may be sparse literature on the illness and even fewer specialists to consult. Yet, in many cases, there are more treatment options or clinical research in different stages the issue is that they are not widely known as the information is not widely shared.

Prior to AI-supported digital technology, the volume of treatments in clinical research environments was difficult for providers to assess as opportunities for their patients. Today, cloud, data and analytics technologies enable healthcare professionals to tailor treatments to a patients specific multi-omic data profile. These tailored treatments can be either pre or post-market, which opens up potentially life-saving clinical trials to patients with rare diseases, as the AI-technology supporting data-driven decisions can guide the physician through the huge volumes of patient data and treatment options. Imagine trying to navigate the internet without the support AI search algorithms and you can understand the challenge facing a physician trying to navigate the modern clinical research options at the same time as their patients multi-omic data profile.

Making Safe Data-Driven Decisions with AI

While AI-powered data analysis makes clinical research more efficient, it does not sacrifice safety for speed. Although manual efforts to analyze clinical research information are reduced, a large amount of data must be collected for accurate algorithm development. Any fragmented or inaccurate data diminishes the positive impact of AI-supported clinical research and could potentially result in unsafe data-driven decisions.

The key to making these patient treatment decisions is analyzing enough diverse data to gain insights into safety signals and the efficacy of new drugs. Disparate data from various sources will inevitably need to be cleaned and standardized for analysis. AI helps to support this process of data collection and preparation by automating the compilation, standardization, and analysis of all the data. This automatically establishes a universal source of truth, without the risk of human error to offset the accuracy of machine-generated insights, for healthcare professionals, regulators, and clinical researchers.

This data synthesis helps to overcome a significant challenge for todays clinical researchers, who must compile reports from HCPs and digital data from labs to get the full picture of a medicines effectiveness and safety. In addition, different countries have different regulatory requirements for handling patient data. For example, European servers must comply with GDPR guidelines, and in China patient data cannot cross the border to another country. Leveraging AI to automate the collection of the appropriate data can ensure that the right information is collected and analyzed to meet regional requirements and ensure patient safety.

Making Clinical Trials Data More Accessible for HCPs & Patients

Clinical researchers and pharmaceutical organizations tend to use digital technology to record and store data, the systems that HCPs use are rarely connected to those used by pharmaceutical organizations. In fact, there are dozens of different computer systems that clinical researchers and physicians use to record information. This situation creates siloed data on both ends of the spectrum. HCPs cannot easily access clinical research information, and researchers cannot easily receive updates on the efficacy of their new treatments from HCPs.

Currently, patients can also seek clinical trials that may offer novel treatments and therapeutic combinations intended to reduce symptoms and the overall burden of disease by visiting ClinicalTrials.gov. However, the website is not particularly patient-friendly and doesnt make finding relevant and potentially effective trials easy for patients that are not medically trained or educated. It is much easier for HCPs to identify clinical trials for their patients, especially when they have access to portable, AI-based technology at their fingertips that could suggest clinical trials for their patients respective illnesses.

Cloud and AI technology allow life science companies and HCPs to collaborate, creating a seamless map of a patients journey through the treatment process to further future research and develop newer and more innovative treatments for rare diseases.

A Better Future for Rare Disease Patients

Today HCPs and clinical research organizations weave together patient and treatment data while leveraging AI analytics,to safely place patients in clinical trials, as well as speed the development and approval of new medicines.This technology allows healthcare professionals to spend more time treating patients, and less time diagnosing their illness and researching a possible treatment. Companies that adopt AI-driven analysis for clinical research will also be better positioned to develop newer and more effective treatments down the line.

About Luca Glass

Lucas Glass is the Vice President of the Analytics Center of Excellence at IQVIA. The Center is responsible for researching, developing and operationalizing machine learning and data science solutions in the R&D business. Lucas started his career in pharmaceutical data science 15 years ago at Center (then owned by Galt Associates), working on pharmacovigilance data mining algorithms. Since then he has worked at the U.S. Department of Justice in healthcare fraud, several small startups, and TTC, LLC, which was acquired by IMS Health in 2012.

Originally posted here:

Using AI to Match Patients with Clinical Trials for Proactive Treatment - HIT Consultant

Read More..

Artificial Intelligence and Deep Learning Models Will Be Used to Protect the Great Barrier Reef – Tech Times

Researchers will now use the power of technologies to monitor and help protect the Great Barrier Reef. Following the photographs taken by citizen scientists, Artificial Intelligence (AI) and deep learning will be used.

Citizens of the Great Barrier Reef recruited boats to help survey over 300 reefs from the tip of Queensland down to Lady Elliot Island in 2020 and early this year, according to ABC. They were able to take 52,000 photos of the reef to see the big picture in regards of its health. They were then asked to help identify problem areas, such as bleach to target better restoration efforts.

Dell has developed a new AI system that will see around 13,000 reef images analyzed a week or approximately one minute per photo. While the Singapore-based data science team worked with universities to develop the Great Reef Census (GRC) technology to identify five crucial coral categories in every image.

The analyzed data will be shared with University of Queensland and James Cook University researchers for better prioritization of reef conservation efforts when the program goes live.

A previously implemented Dell edge solution deployed on watercraft was able to upload data automatically to the deep learning model through a mobile network for real-time image capture. With this, it will enhance the capabilities of the Great Reef Census as it speeds up image analysis. Also, the new model will be able to analyze the same data set in less than 200 hours.

The initiative aligns Dell's Environmental, Social and Governance (ESG) ambitions to boost sustainability through the creation of technology that drives progress, and working with partners, customers, suppliers, and communities to promote climate action.

Also Read: Artificial Intelligence vs. Poachers: How AI Can Help Protect Endangered Animals

According to BW Businessworld, Dell has developed the model for GRC over the last five months by model by prioritizing core categories, understanding the dataset, cleaning the dataset, and building hundreds of models with different model architectures and hyperparameters.

"This deep learning still relies on human input: someone of the reef takes a photo, and the deep learning model defines the coral outline and health status; then, someone else can check the outline and confirm the label before the data is sent to the University of Queensland," said Aruna Kolluru, the Chief Technologist, Emerging Technology, Dell technologies, Asia Pacific and Japan.

Over the past 30 years, the Great Barrier Reef has been hit with mass bleaching. Based on the current rate, the Great Barrier Reef is facing an extinction of coral.The Great Barrier Reef could have passed the point of no return and could be on track to disappear in as little as 50 years. With this latest technologies, we could save it.

Related Article: New Artificial Intelligence Light System May Be the Answer to Traffic Congestion

This article is owned by Tech Times.

Written by: April Fowell

2022 TECHTIMES.com All rights reserved. Do not reproduce without permission.

See the original post here:
Artificial Intelligence and Deep Learning Models Will Be Used to Protect the Great Barrier Reef - Tech Times

Read More..

Quantum computing is an even bigger threat than artificial intelligence – here’s why – WRAL TechWire

Compounding the danger is the lack of anyAI regulation. Instead, unaccountable technology conglomerates, such as Google and Meta, have assumed the roles of judge and jury in all things AI. They are silencing dissenting voices, including their own engineers who warn of the dangers.

The worlds failure to rein in the demon of AIor rather, the crude technologies masquerading as suchshould serve to be a profound warning. There is an even more powerful emerging technology with the potential to wreak havoc, especially if it is combined with AI:quantum computing. We urgently need to understand this technologys potential impact, regulate it, and prevent it from getting into the wrong hands before it is too late. The world must not repeat the mistakes it made by refusing to regulate AI.

Although still in its infancy, quantum computing operates on a very different basis from todays semiconductor-based computers. If thevarious projectsbeing pursued around the world succeed, these machines will be immensely powerful, performing tasks in seconds that would takeconventional computersmillions of years to conduct.

Because of the technologys immense power and revolutionary applications, quantum computing projects are likely part of defense and other government research already.

Semiconductors represent information as a series of 1s and 0sthats why we call it digital technology. Quantum computers, on the other hand, use a unit of computing called aqubit. A qubit can hold values of 1 and 0 simultaneously by incorporating a counterintuitive property in quantum physics called superposition. (If you find this confusing, youre in good companyit can be hard to grasp even for experienced engineers.) Thus, two qubits could represent the sequences 1-0, 1-1, 0-1, and 0-0, all in parallel and all at the same instant. That allows a vast increase in computing power, which grows exponentially with each additional qubit.

Quantum computing researchers at Duke observe tipping point

If quantum physics leaves the experimental stage and makes it into everyday applications, it will find many uses and change many aspects of life. With their power to quickly crunch immense amounts of data that would overwhelm any of todays systems,quantum computerscould potentially enable better weather forecasting, financial analysis, logistics planning, space research, and drug discovery. Some actors will very likely use them for nefarious purposes, compromising bank records, private communications, and passwords on every digital computer in the world. Todays cryptography encodes data in large combinations of numbers that are impossible to crack within a reasonable time using classic digital technology. But quantum computerstaking advantage of quantum mechanical phenomena, such as superposition, entanglement, and uncertaintymay potentially be able to try out combinations so rapidly that they could crack encryptions by brute force almost instantaneously.

To be clear, quantum computing is still in an embryonic stagethough where, exactly, we can only guess. Because of the technologys immense potential power and revolutionary applications, quantum computing projects are likely part of defense and other government research already. This kind of research isshrouded in secrecy, and there are a lot of claims and speculation about milestones being reached. China, France, Russia, Germany, the Netherlands, Britain, Canada, and India are known to be pursuing projects. In the United States, contenders include IBM, Google, Intel, and Microsoft as well as various start-ups, defense contractors, and universities.

Despite the lack of publicity, there have been credible demonstrations of some basic applications, includingquantum sensorsable to detect and measure electromagnetic signals. One such sensor was used to precisely measureEarths magnetic fieldfrom the International Space Station.

IBM unveils roadmap for developing quantum-powered supercomputers

In another experiment, Dutch researchers teleported quantum information across a rudimentaryquantum communication network. Instead of using conventional optical fibers, the scientists used three small quantum processors to instantly transfer quantum bits from a sender to a receiver. These experiments havent shown practical applications yet, but they could lay the groundwork for a future quantum internet, where quantum data can be securely transported across a network of quantum computers faster than the speed of light. So far, thats only been possible in the realm of science fiction.

The Biden administration considers the risk of losing the quantum computing race imminent and dire enough that it issuedtwo presidential directivesin May: one to place theNational Quantum Initiativeadvisory committee directly under the authority of the White House and another to directgovernment agenciesto ensure U.S. leadership in quantum computing while mitigating the potential security risks quantum computing poses to cryptographic systems.

Experiments are also working tocombinequantum computing with AI to transcend traditional computers limits. Today, large machine-learning models take months to train on digital computers because of the vast number of calculations that must be performedOpenAIs GPT-3, for example, has 175 billion parameters. When these models grow into the trillions of parametersa requirement for todays dumb AI to become smartthey will take even longer to train. Quantum computers could greatly accelerate this process while also using less energy and space. In March 2020, Google launchedTensorFlowQuantum, one of the first quantum-AI hybrid platforms that takes the search for patterns and anomalies in huge amounts of data to the next level.Combined with quantum computing, AI could, in theory, lead to even more revolutionary outcomes than the AI sentience that critics have been warning about.

Quantum breakthrough? Duke, IonQ invent means to accelerate key quantum techniques

Given the potential scope and capabilities ofquantum technology, it is absolutely crucial not to repeat the mistakes made with AIwhere regulatory failure has given the world algorithmic bias that hypercharges human prejudices, social media that favors conspiracy theories, and attacks on the institutions of democracy fueled by AI-generated fake news and social media posts. The dangers lie in the machines ability to make decisions autonomously, with flaws in the computer code resulting in unanticipated, often detrimental, outcomes. In 2021, the quantum community issued acall for actionto urgently address these concerns. In addition, critical public and private intellectual property on quantum-enabling technologies must be protected fromtheft and abuseby the United States adversaries.

There are national defense issues involved as well. In security technology circles, the holy grail is whats called acryptanalytically relevant quantum computera system capable of breaking much of the public-key cryptography that digital systems around the world use, which would enable blockchain cracking, for example. Thats a very dangerous capability to have in the hands of an adversarial regime.

Experts warn thatChinaappears to have a lead in various areas of quantum technology, such as quantum networks and quantum processors. Two of the worlds most powerful quantum computers were beenbuilt in China, and as far back as 2017, scientists at the University of Science and Technology of China in Hefei built the worlds firstquantum communication networkusing advanced satellites. To be sure, these publicly disclosed projects are scientific machines to prove the concept, with relatively little bearing on the future viability of quantum computing. However, knowing that all governments are pursuing the technology simply to prevent an adversary from being first, these Chinese successes could well indicate an advantage over the United States and the rest of the West.

Beyond accelerating research, targeted controls on developers, users, and exports should therefore be implemented without delay. Patents, trade secrets, and relatedintellectual property rightsshould be tightly secureda return to the kind of technology control that was a major element of security policy during the Cold War. The revolutionary potential of quantum computing raises the risks associated withintellectual property theftby China and other countries to a new level.

Exec shares six predictions for quantum computing industry in 2022

Finally, to avoid theethical problemsthat went so horribly wrong with AI and machine learning, democratic nations need to institute controls that both correspond to the power of the technology as well as respect democratic values, human rights, and fundamental freedoms. Governments must urgently begin to think about regulations,standards, and responsible usesand learn from the way countries handled or mishandled other revolutionary technologies, including AI, nanotechnology, biotechnology, semiconductors, and nuclear fission. The United States and otherdemocratic nationsmust not make the same mistake they made with AIand prepare for tomorrows quantum era today.

About the authors

Vivek Wadhwais a columnist atForeign Policy, an entrepreneur, and the co-author ofFrom Incremental to Exponential: How Large Companies Can See the Future and Rethink Innovation.Twitter:@wadhwa

Mauritz Kopis a fellow and visiting scholar at Stanford University.Twitter:@MauritzKop

Duke Quantum Center officially opens, offering a look at computings future

Visit link:
Quantum computing is an even bigger threat than artificial intelligence - here's why - WRAL TechWire

Read More..

Headroom Solves Virtual Meeting Fatigue with Artificial Intelligence that Eliminates Wasted Time and Reveals Essential Highlights – Business Wire

SAN FRANCISCO--(BUSINESS WIRE)--Headroom, a meeting platform leveraging artificial intelligence to improve communications and productivity, today announced a $9 million investment led by Equal Opportunity Ventures with participation from Gradient Ventures, LDV Capital, AME Cloud Ventures and Morado Ventures. The capital brings total funding to date to $14 million and will be used to expand Headrooms team, product development and mobile offering. The company also recently added new Shareable Automatic Summaries to its suite of tools for remote and hybrid meetings, furthering its mission to support balanced, entertaining, productive and memorable meetings.

Virtual meetings have become the de facto method for gathering, connection and collaboration. According to Fortune Business Insights, the meeting collaboration market is expected to exceed $41 billion by 2029. Gartner predicts that by 2025, 75% of conversations at work will be recorded and analyzed, enabling the discovery of added organizational value or risk. Yet despite the increase in meetings, productivity and engagement rates are down. Even before the start of the pandemic, a Harvard Business Review survey revealed 65% of senior managers felt meetings kept them from completing their own work and 64% said meetings come at the expense of deep thinking. Smarter meetings may be the biggest opportunity for improved work productivity and satisfaction.

The more meetings held, the more time wasted, with too many people spending time in redundant meetings. Headroom is leveraging AI to help companies do more with less, enabling individual workers to be more productive, choose which meetings to attend and which to watch later, or just quickly get the key pieces of information discussed, said Julian Green, CEO and Co-Founder of Headroom. Particularly in this environment, where for startups every dollar and every meeting minute counts, those that can move faster and stay better connected with people wherever they are, in real time and asynchronously, will win.

Headroom is self-learning; its relevance and impact on productivity improves with use. Headroom data shows 90% of every meeting lacks useful information. To maximize the 10% meeting content that is helpful, the company developed Shareable Automatic Summaries which auto-generate highlight reels that provide key moments, shared notes and action items, and enable easy sharing with others. Additional platform functionality that maximizes synchronous and asynchronous communication includes:

"Hybrid work is here to stay and virtual meetings are the norm, but they allow for a wide margin of distraction," said Roland Fryer, Founder and Managing Partner at Equal Opportunity Ventures and newly appointed Headroom Board Member. Headroom at its core is an engagement and productivity platform - streamlining collaboration and information sharing, without a heavy lift. It saves time in scheduling, reporting and collaborating."

Simply put: meetings should be better. Unlike any other video communication and collaboration platform, Headroom is stateful. Meeting information is generated during live conversations, and can be augmented and accessed forever after. Participants are free to act naturally and engage with the information without being restricted by the actual meeting slot, said Andrew Rabinovich CTO and Co-Founder of Headroom. Those who didn't attend the meeting itself, have all the details readily available to them. With Headroom, this is automated and highlights go to non-attendee stakeholders who can replay key decisions. Our customers are also using it as an information resource they can search for key information later.

Headroom was co-founded by Julian Green and Andrew Rabinovich in 2020. The companys executive team experience spans founding and leadership roles at GoogleX, Houzz, Magic Leap, Patreon and Square. Headrooms platform currently serves more than 5,000 customers spanning technology and online education startups, as well as marketing, design, consulting and recruiting agencies. It is free with no usage caps or storage limits, and is available on Google Chrome with no download or app required. Users have full control over sharing of meeting information. Get started at https://www.goheadroom.com/.

ABOUT HEADROOM

Headroom, founded in 2020, is improving communication in meetings by augmenting meeting intelligence. Automated virtual meetings in Headroom allow attendees to act naturally, replay key decisions, build smart summaries and search everything later. Headroom is brought to you by an experienced team that has created and managed AI products used by billions of people at tech startups and large companies including Google and Magic Leap. The founders helped create the worlds leading Computer Vision, Augmented Reality and Virtual Reality products, started Unicorns, and have won a Webby. To get started with Headroom visit https://www.goheadroom.com/.

Excerpt from:
Headroom Solves Virtual Meeting Fatigue with Artificial Intelligence that Eliminates Wasted Time and Reveals Essential Highlights - Business Wire

Read More..

Chips-Plus Artificial Intelligence in the CHIPS Act of 2022 – Lexology

On August 9, 2022, President Biden signed the CHIPS Act of 2022 (the Act), legislation to fund domestic semiconductor manufacturing and boost federal scientific research and development (see our previous alert for additional background). As part of its science-backed provisions, the Act includes many of the U.S. Innovation and Competition Acts (USICA) original priorities, such as promoting standards and research and development in the field of artificial intelligence (AI) and supporting existing AI initiatives.

National AI Initiative

The Act directs the National Institute of Standards and Technology (NIST) Director to continue supporting the development of AI and data science and to carry out the National AI Initiative Act of 2020 (previous alert for additional background), which created a coordinated program across the federal government to accelerate AI research and application to support economic prosperity, national security, and advance AI leadership in the United States. The Director will further the goals of the National AI Initiative Act of 2020 by:

Furthermore, the Act provides that the Director may establish testbeds, including in virtual environments, in collaboration with other federal agencies, the private sector and colleges and universities, to support the development of robust and trustworthy AI and machine learning systems.

NSF Directorate for Technology, Innovation and Partnerships

A new National Science Foundation (NSF) Directorate for Technology, Innovation and Partnerships (the Directorate) is established under the Act to address societal, national and geostrategic challenges for the betterment of all Americans through research and development, technology development and related solutions. Over the next five years, the new Directorate will receive $20 billion in funding. Moreover, the Directorate will focus on 10 key technology focus areas, including AI, machine learning, autonomy, related advances, robotics, automation, advanced manufacturing and quantum computing, among other areas.

DOE Research, Development and Demonstration Activities

Within the Department of Energy (DOE), the Act authorizes $11.2 billion for research, development and demonstration activities and to address energy-related supply chain activities in the ten key technology focus areas prioritized by the new NSF Directorate. Further, the Act authorizes $200 million for the DOEs Office of Environmental Management to conduct research, development and demonstration activities, including the fields of AI and information technology.

Federal AI Scholarship in Graduate Education

The Act directs NSF Director to submit to the relevant House and Senate congressional committees a report outlining the need, feasibility and plans for implementing a program for recruiting and training the next generation of AI professionals. The report will evaluate the feasibility of establishing a federal AI scholarship-for-service program to recruit and train the next generation of AI professionals.

See the article here:
Chips-Plus Artificial Intelligence in the CHIPS Act of 2022 - Lexology

Read More..

The era of the Artificial-Intelligence fashion designer is getting closer – Times of India

The industries are flourishing and expanding and the technological advancements in the fashion industry are growing exponentially. With passing time, personalization has gotten much attention and has become one of the biggest trends, and Artificial Intelligence in the industry is finding out new ways to analyze all the data and tailor designs according to peoples preferences.

Artificial Intelligence in fashion market

AI has already acquired its position in the fashion market and is growing at a rapid pace. Globally, the market size of AI in the fashion market is estimated to grow to USD 1260 million by 2024 from USD 228 million in the year 2019 that is growing at a CAGR of 40.8% between the year 2019-2024.

The future of AI in the Fashion industry grows stronger and stronger as the demand from the customer to have a personalized experience, demand from the inventory management also plays a role in encouragement of the growth of AI in the fashion market. Apart from this, influence and support on social media is backing the use of AI in fashion designing.

Artificial Intelligence helps the fashion sector by identifying the desired future trends by analyzing the consumers purchasing behavior. AI also helps to boost the concept of fast fashion and enables vendors to use AI for solutions revolving fashion.

Fashion design for everyone

In present conditions, every design sector requires a certain level of creative and social intelligence from the designers. Some of the skills that are demanded from fashion designers are creative problem solving, negotiation, persuasion, empathy and many more. AI helps to enable these skill sets into a designer thus creating scope for a large number of non-designers to enhance their skills and boost employability.

The process of design thinking in fashion plays a crucial role as the power moves from the hands of the designer into the hands of the audience. Fashion design is no longer a sector that is related only to creating designs and transforming it into its true form instead modern fashion design has given its importance to everyone.

With the help of the AI, designers try to learn the customers behavior and persona, analyse patterns of behavior based on the data collected, enhance the process of developing design principles and test the prototype based on those principles.

Switch to virtual design

Virtual fashion design is a new trending aspect in the field of sustainable fashion. Virtual fashion design is faster than traditional methods and shows realistic 3D samples than the traditional physical samples. Virtual design in fashion is the most beneficial use of AI as it reduces the waste of cloth as it can sew, unsew, apply any color or fabric, design on the virtual design without any wastage of materials.

Virtual fashion design has grown exponentially during Covid times as it proved to be beneficial for remote development as well. As per statistics, virtual designs reduce the cost by 30% as they save time developing the designs virtually. Virtual fashion design creates 3D images that are realistic and accurate, reduces waste of unusable samples, reduces the use of harmful processes in fabric and material such as dying and most importantly reduces pollution that causes due to shipment of samples.

Enhanced fashion designs

Artificial Intelligence has enhanced the fashion designing industry greatly, from designers working for weeks to bring out a sample with huge wastage of time and supply; now with the help of AI, designs are produced daily at a larger scale than with the help of traditional methods.

Artificial Intelligence is implemented in the fashion industry for better analysis of customer requirements. It benefits the industry by scanning a precise body and making appropriate measurements using smartphone pictures. AI helps in enhancing the fashion designing industry by creating a styling guide based on the recommendations of the people. Small retailers are also benefited as they can figure out the trends in the market and have a chance to meet the demands of the consumer.

The advances in technology are bringing designs to a new and enhanced place where we also see AI playing a new role. The industry is changing and the new programs that come along with AI are making the fashion industry more intelligent.

Views expressed above are the author's own.

END OF ARTICLE

Follow this link:
The era of the Artificial-Intelligence fashion designer is getting closer - Times of India

Read More..

The Global Mobile Artificial Intelligence (AI) Market is expected to grow by $ 23.61 bn during 2022-2026, accelerating at a CAGR of 29.06% during the…

ReportLinker

Global Mobile Artificial Intelligence (AI) Market 2022-2026 The analyst has been monitoring the mobile artificial intelligence (AI) market and it is poised to grow by $ 23. 61 bn during 2022-2026, accelerating at a CAGR of 29.

New York, Aug. 24, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Mobile Artificial Intelligence (AI) Market 2022-2026" - https://www.reportlinker.com/p06315915/?utm_source=GNW 06% during the forecast period. Our report on the mobile artificial intelligence (AI) market provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors.The report offers an up-to-date analysis of the current global market scenario, the latest trends and drivers, and the overall market environment. The market is driven by increasing smartphone penetration, increasing capital investments in AI start-ups, and increasing demand for AI in enterprise applications.The mobile artificial intelligence (AI) market analysis includes application segment and geographic landscape.

The mobile artificial intelligence (AI) market is segmented as below:By Application Smartphone Camera Automotive Robotics Others

By Geographical Landscape North America Europe APAC South America The Middle East and Africa

This study identifies the increasing demand for edge computing in IoT as one of the prime reasons driving the mobile artificial intelligence (AI) market growth during the next few years. Also, growing investments in 5G network and an increasing number of acquisitions and partnerships will lead to sizable demand in the market.

The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters. Our report on the mobile artificial intelligence (AI) market covers the following areas: Mobile artificial intelligence (AI) market sizing Mobile artificial intelligence (AI) market forecast Mobile artificial intelligence (AI) market industry analysis

This robust vendor analysis is designed to help clients improve their market position, and in line with this, this report provides a detailed analysis of several leading mobile artificial intelligence (AI) market vendors that include AIStorm Inc, Alphabet Inc., Apple Inc., Blaize, Cerebras Systems Inc, CrossCert, Fuzhou Rockchip Electronics Co. Ltd., Graphcore Ltd., Huawei Technologies Co. Ltd., Imagination Technologies Ltd, Intel Corp., International Business Machines Corp., MediaTek Inc., NVIDIA Corp., Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc, Think Force, and Xilinx Inc. Also, the mobile artificial intelligence (AI) market analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to an analysis of the key vendors.

The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters such as profit, pricing, competition, and promotions. It presents various market facets by identifying the key industry influencers. The data presented is comprehensive, reliable, and a result of extensive research - both primary and secondary. Technavios market research reports provide a complete competitive landscape and an in-depth vendor selection methodology and analysis using qualitative and quantitative research to forecast accurate market growth.Read the full report: https://www.reportlinker.com/p06315915/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

__________________________

Story continues

Read the original:
The Global Mobile Artificial Intelligence (AI) Market is expected to grow by $ 23.61 bn during 2022-2026, accelerating at a CAGR of 29.06% during the...

Read More..

Researchers Using Artificial Intelligence to Assist With Early Detection of Autism Spectrum Disorder – University of Arkansas Newswire

Photo by University Relations

Khoa Luu and Han-Seok Seo

Could artificial intelligence be used to assist with the early detection of autism spectrum disorder? Thats a question researchers at the University of Arkansas are trying to answer. But theyre taking an unusual tack.

Han-Seok Seo, an associate professor with a joint appointment in food science and the UA System Division of Agriculture, and Khoa Luu, an assistant professor in computer science and computer engineering, will identify sensory cues from various foods in both neurotypical children and those known to be on the spectrum. Machine learning technology will then be used to analyze biometric data and behavioral responses to those smells and tastes as a way of detecting indicators of autism.

There are a number of behaviors associated with ASD, including difficulties with communication, social interaction or repetitive behaviors. People with ASD are also known to exhibit some abnormal eating behaviors, such as avoidance of some if not many foods, specific mealtime requirements and non-social eating. Food avoidance is particularly concerning, because it can lead to poor nutrition, including vitamin and mineral deficiencies. With that in mind, the duo intend to identify sensory cues from food items that trigger atypical perceptions or behaviors during ingestion. For instance, odors like peppermint, lemons and cloves are known to evoke stronger reactions from those with ASD than those without, possibly triggering increased levels of anger, surprise or disgust.

Seo is an expert in the areas of sensory science, behavioral neuroscience, biometric data and eating behavior. He is organizing and leading this project, including screening and identifying specific sensory cues that can differentiate autistic children from non-autistic children with respect to perception and behavior. Luu isan expert in artificial intelligence with specialties in biometric signal processing, machine learning, deep learning and computer vision. He will develop machine learning algorithms for detecting ASD in children based on unique patterns of perception and behavior in response to specific test-samples.

The duo are in the second year of a three-year, $150,000 grant from the Arkansas Biosciences Institute.

Their ultimate goalis to create an algorithm that exhibits equal or better performance in the early detection of autism in children when compared to traditional diagnostic methods, which require trained healthcare and psychological professionals doing evaluations, longer assessment durations, caregiver-submitted questionnaires and additional medical costs. Ideally, they will be able to validate a lower-cost mechanism to assist with the diagnosis of autism. While their system would not likely be the final word in a diagnosis, it could provide parents with an initial screening tool, ideally eliminating children who are not candidates for ASD while ensuring the most likely candidates pursue a more comprehensive screening process.

Seo said that he became interested in the possibility of using multi-sensory processing to evaluate ASD when two things happened: he began working with a graduate student, Asmita Singh, who had background in working with autistic students, and the birth of his daughter. Like many first-time parents, Seo paid close attention to his newborn baby, anxious that she be healthy. When he noticed she wouldnt make eye contact, he did what most nervous parents do: turned to the internet for an explanation. He learned that avoidance of eye contact was a known characteristic of ASD.

While his child did not end up having ASD, his curiosity was piqued, particularly about the role sensitivities to smell and taste play in ASD. Further conversations with Singh led him to believe fellow anxious parents might benefit from an early detection tool perhaps inexpensively alleviating concerns at the outset. Later conversations with Luu led the pair to believe that if machine learning, developed by his graduate student Xuan-Bac Nguyen, could be used to identify normal reactions to food, it could be taught to recognize atypical responses, as well.

Seo is seeking volunteers 5-14 years old to participate in the study. Both neurotypical children and children already diagnosed with ASD are needed for the study. Participants receive a $150 eGift card for participating and are encouraged to contact Seo athanseok@uark.edu.

About the University of Arkansas:As Arkansas' flagship institution, the UofA provides an internationally competitive education in more than 200 academic programs. Founded in 1871, the UofA contributes more than$2.2 billion to Arkansas economythrough the teaching of new knowledge and skills, entrepreneurship and job development, discovery through research and creative activity while also providing training for professional disciplines. The Carnegie Foundation classifies the UofA among the few U.S. colleges and universities with the highest level of research activity.U.S. News & World Reportranks the UofA among the top public universities in the nation. See how the UofA works to build a better world atArkansas Research News.

See the rest here:
Researchers Using Artificial Intelligence to Assist With Early Detection of Autism Spectrum Disorder - University of Arkansas Newswire

Read More..