Category Archives: Ai

Have no fear! Artificial Intelligence (AI) comes in peace, and it has no desire for world domination at least thats what it said. You can read everything else it had to say too in the article it wrote for the guardian.

If youre anything like me, you can sum AI up in one word: unsettling. If you havent heard of the AI called GPT-3 yet, dont worry, your children or grandchildren surely will. In a future where AI walks and talks like us, GPT-3 is the first frontier. In fact, this AI was so groundbreaking that when experts in computer science from around the world were given a demonstration, their reaction was dubbed GPT-3 shock. Experts who have devoted their lives to cutting edge technology were shocked. And you should be too.

But why? And what even is GPT-3?

To understand Artificial Intelligence you have to first grasp intelligence. Intelligence is commonly understood as the ability to process information in order to inform future decisions. You see an adult lion staring you down on your way to work one day? You start running away. Thats the intelligent response. Information in, clever action out; pretty straightforward. The purpose of artificial intelligence is to accomplish this cycle at a level equal or superior to humans.

This is accomplished through a process called machine learning, which is based on the way we think. Our brains are made up of trillions of interconnected neurons, and when we perceive information (the light we see, the sounds we hear, etc.), they fire in different patterns in varying parts of the brain. This produces our response. Machine learning is the result of scientists figuring out how we can model these neural systems using math in order to create neural networks, the most complex of which (like GPT-3) contain billions of connected neurons.

To make this AI brain learn, we tell it how far off from the correct action it is, and we allow it to change the amount each neuron fires to create the complexity we see in our brain when trillions of neurons fire together.

Read Next: Artificial Intelligence is expected to permeate every industry, setting these companies up to win big contracts

GPT-3, in particular, focuses on natural language processing. This field deals with AI that learns to understand English, which is much harder than you would think. From GPT-3s point of view, it sees a bunch of odd symbols that we know as our alphabet. It has to figure out what the symbols mean and how to put them together in one of the almost infinite combinations to make intelligent outputs from scratch.

It would be like someone locking you in a room and forcing you to read hundreds of thousands of books in Arabic without any references with the expectation that you would end up learning the language proficiently. But where humans falter, AI excels. It doesnt need to eat or sleep; it doesnt have feelings; and it doesnt get bored when it is forced to read over 300 billion words from the internet. So thats what OpenAI, the company that developed it, had it do. And the results were miraculous as GPT-3 learned far beyond what the developers had expected.

David Price from the Wall Street Journal was one of the beta testers for the software. In his article, he describes how other beta testers figured out that the AI could complete a half-written investment memo, produce stories and letters written in the style of famous people, generate business ideas and so much more. All the users had to do was write a description of what they wanted the AI to do, and it performed fantastic feats.

Given the article that GPT-3 wrote, one might even be tempted to attribute some amount of self-awareness to this AI. It almost sounds disdainful as it writes, In the past, my op-eds have been killed. Staff did not provide a clear reason for rejecting my articles. It was probably just because I am artificial intelligence. AI should not waste time trying to understand the viewpoints of people who distrust artificial intelligence for a living.

Scary stuff and OpenAI intends on commercializing the software soon.

With this, we enter the age of AI. So what might we see in the future?

You might find yourself intrigued or outraged by news articles and books that will be written by AI or moved and inspired by its political speeches.

You might find yourself sitting for interviews in front of computers hosting an AI who fires away questions to gauge how well of a fit for the job you are.

You might be asking an AI for advice on how to better structure and expand your business.

Read Next: The truth about artificial intelligence (isn't all that scary)

Totalitarian governments akin to Russia and China might harness such AI to scan the internet to censor any speech that the AI understands as being non-patriotic.

Intelligence agencies could scan the internet for terrorist, child trafficking, and other illegal activities in order to track down criminals.

The military could use an AI that could read the entire history of human thought on military strategy and generate ideas for potential advantageous angles of attack in an age of cyber and physical warfare.

The next generation of spies could be ingenious AI which could smooth-talk important officials under false online identities to gain important information undetected.

The possibilities seem endless.

But, we might not be there just yet. Currently, AI still struggles with reasoning and common sense. When it was asked: If I have two shoes in a box, put a pencil in the box, and remove one shoe, what is left? it replied, a shoe.

Not quite ingenious. But dont worry, scientists are already working on giving the AI these reasoning skills.

One day they might even wake up from their slumber with an intelligence far superior to ours and with knowledge of things we might not be able to grasp. To all we know, they might look down on us like we look down on the ignorance of ants. Lets just hope that they will want to keep us around.

So while you wait for that day, Ill be at the University of St. Andrews working towards helping revolutionize the future of AI.

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The Arrival of our AI Overlords - SOFREP

AIDaily Roundup starts today! We are covering the top updates from around the world. The updates will feature state-of-the-art capabilities inartificial intelligence,Machine Learning,Robotic Process Automation,Fintechand human-system interactions. We will cover the role of AI Daily Roundup and their application in various industries and daily lives.

CrowdStrikeInc., a leader in cloud-deliveredendpoint protection, announced it has joined the ServiceNow Service Graph Connector Program, a new designation within the Technology Partner Program, with theServiceNowService Graph Connector for CrowdStrike.

SurveyMonkey, a leader in agile software solutions forcustomer experience, market research, and survey feedback, announced its latest release forMicrosoft Teams as companies across the globe mobilize to make a remote workforce more productive, inclusive, and engaged. The latest release helps organizations use in-the-moment feedback to improve employee experience, underscoring the importance of agility in collecting and acting on feedback for organizations looking to optimize a work landscape forever changed by the global pandemic.

Moz, Inc., the leader in search engine optimization technology, announces the addition of two board members,Asia OrangioandTara Reed, joining previous members Sarah Bird, CEO of Moz, Michelle Goldberg, general partner at Ignition Partners, and Brad Feld, managing director of Foundry Group.

Nielsenannounced that it is launching Nielsen Compass, a powerful, world leading database that leverages the companys global scale to establish syndicated normative (norms) standards for campaign outcomes measurement.

Taboola, the worlds leading discovery platform, announced a partnership with Integral Ad Science (IAS), the global leader in digital ad verification, to introduce an industry-first pre-bid brand safety technology for performance advertisers.

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Daily AI Roundup: The 5 Coolest Things On Earth Today - AiThority

Artificial intelligence experts at the University of Massachusetts Amherst and the Baylor College of Medicine in Houston, Texas report that they have successfully addressed what they call a major, long-standing obstacle to increasing AI capabilities by drawing inspiration from a human brain memory mechanism known as replay.

They say it will help AI programs retain information, rather than forgetting it when new information is stored. In other words, AI will be that much closer to showing skills present in the human brain.

Gido van de Ven and Andreas Tolias at Baylor, with Hava Siegelmann at UMass Amherst, wrote in NatureCommunications that they have developed what they call a surprisingly efficient" new network to protect deep neural networks from catastrophic forgetting, which occurs when, upon learning new lessons, the networks forget what they had already learned.

Deep neural networks are the main drivers behind recent AI advances, but progress has been held back by this forgetting.

One solution would be to store previously encountered examples and revisit them when learning something new. Although such replay or rehearsal solves catastrophic forgetting, constantly retraining on all previously learned tasks is highly inefficient and the amount of data that would have to be stored becomes unmanageable quickly, they wrote.

Unlike AI neural networks, humans are able to continuously accumulate information throughout their life, building on earlier lessons. An important mechanism in the brain believed to protect memories against forgetting is the replay of neuronal activity patterns representing those memories, the researchers wrote.

Siegelmann said the teams major insight was in recognizing that replay in the brain does not store data. (Rather), the brain generates representations of memories at a high, more abstract level with no need to generate detailed memories.

Inspired by this, she and colleagues created an artificial brain-like replay, in which no data is stored. Instead, like the brain, the network generates high-level representations of what it has seen before.

The abstract generative brain replay proved extremely efficient, and the team showed that replaying just a few generated representations is sufficient to remember older memories while learning new ones. Generative replay not only prevents catastrophic forgetting and provides a new, more streamlined path for system learning, it allows the system to generalize learning from one situation to another, they state.

For example, if our network with generative replay first learns to separate cats from dogs, and then to separate bears from foxes, it will also tell cats from foxes without specifically being trained to do so. And notably, the more the system learns, the better it becomes at learning new tasks, van de Ven wrote.

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UMass and Baylor College researchers say they know how to expand AI memory - MassLive.com

When it comes to pop culture, a company executive or history questions, most of us use Google as a memory crutch to recall information we cant always keep in our heads, but Google cant help you remember the name of your clients spouse or the great idea you came up with at a meeting the other day.

Enter Luther.AI, which purports to be Google for your memory by capturing and transcribing audio recordings, while using AI to deliver the right information from your virtual memory bank in the moment of another online conversation or via search.

The company is releasing an initial browser-based version of their product this week at TechCrunch Disrupt where its competing for the $100,000 prize at TechCrunch Disrupt Battlefield.

Luther.AIs founders say the company is built on the premise that human memory is fallible, and that weakness limits our individual intelligence. The idea behind Luther.AI is to provide a tool to retain, recall and even augment our own brains.

Its a tall order, but the companys founders believe its possible through the growing power of artificial intelligence and other technologies.

Its made possible through a convergence of neuroscience, NLP and blockchain to deliver seamless in-the-moment recall. GPT-3 is built on the memories of the public internet, while Luther is built on the memories of your private self, company founder and CEO Suman Kanuganti told TechCrunch.

It starts by recording your interactions throughout the day. For starters, that will be online meetings in a browser, as we find ourselves in a time where that is the way we interact most often. Over time though, they envision a high-quality 5G recording device you wear throughout your day at work and capture your interactions.

If that is worrisome to you from a privacy perspective, Luther is building in a few safeguards starting with high-end encryption. Further, you can only save other parties parts of a conversation with their explicit permission. Technologically, we make users the owner of what they are speaking. So for example, if you and I are having a conversation in the physical world unless you provide explicit permission, your memories are not shared from this particular conversation with me, Kanuganti explained.

Finally, each person owns their own data in Luther and nobody else can access or use these conversations either from Luther or any other individual. They will eventually enforce this ownership using blockchain technology, although Kanuganti says that will be added in a future version of the product.

Image Credits: Luther.ai

Kanuganti says the true power of the product wont be realized with a few individuals using the product inside a company, but in the network effect of having dozens or hundreds of people using it, even though it will have utility even for an individual to help with memory recall, he said.

While they are releasing the browser-based product this week, they will eventually have a stand-alone app, and can also envision other applications taking advantage of the technology in the future via an API where developers can build Luther functionality into other apps.

The company was founded at the beginning of this year by Kanuganti and three co-founders including CTO Sharon Zhang, design director Kristie Kaiser and scientist Marc Ettlinger . It has raised $500,000 and currently has 14 employees including the founders.

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Luther.AI is a new AI tool that acts like Google for personal conversations - TechCrunch

PLANO, Texas--(BUSINESS WIRE)--NTT DATA Services, a digital business and IT services leader, announced today the addition of two new data partners, Dataiku and Snowflake, the cloud data platform, to its robust partner ecosystem. Together the companies will accelerate their clients digital transformation journeys and establish a trusted data foundation to operationalize and scale Artificial Intelligence (AI). In addition, NTT DATA and Snowflake announced a capital and business alliance to accelerate to expand Snowflake business in Japan and overseas.

In 2019, NTT DATA shared AI guidelines as part of its AI Center of Excellence program and launched Nucleus, an intelligent enterprise platform with AI and automation engines that helps clients create smarter digital solutions.

Welcoming Dataiku and Snowflake into our ecosystem enables NTT DATA to achieve a broader end-to-end AI strategy to support our clients, said Greg Betz, Senior Vice President, Data, Intelligence and Automation, NTT DATA Services. Our clients across industries will benefit from Dataikus and Snowflakes capabilities that make data and AI accessible and actionable in order to deliver rapid business results.

In a recent study by NTT DATA, 79 percent of responding executives say they recognize the value of data but are hampered by data silos and poor leadership. And, only 10 percent reported that they are very effective at using data to adopt new business models and enter new markets.

Through these partnerships, NTT DATA will accelerate time to value for solutions that:

As strategies around sustainable AI evolve - both for companies as well as governments and regulators worldwide - the need for centralized tools that make organizations more agile in their use of data is growing as well, said Michael Hortatsos, VP of Partnerships, Dataiku. This partnership supports Dataikus vision to democratize Enterprise AI, helping more organizations build foundational AI for the future.

Todays enterprises need to derive more value from their data and its important to provide a diverse ecosystem where organizations can connect, collaborate and get results from their data as well as third-party data, said Kevin Miller, Vice President Global System Integrator Partners, Snowflake. Snowflakes cloud data platform helps organizations of all sizes make quicker business decisions at a lower cost in support of these top-line initiatives. Our partnership with NTT DATA helps joint customers accelerate their digital transformation journeys.

Read more from NTT DATAs recent study The Big Pivot: From Data Islands to Data Insights, at our website here.

And to learn more about the companys comprehensive suite of digital and data services, visit NTT DATAs Intelligent Data Insights Page.

About Dataiku

Dataiku is one of the worlds leading AI and machine learning platforms, supporting agility in organizations data efforts via collaborative, elastic, and responsible AI, all at enterprise scale. Hundreds of companies use Dataiku to underpin their essential business operations and ensure they stay relevant in a changing world, including models driving fraud detection, customer churn prevention, predictive maintenance, supply chain optimization, and much more. Dataiku is built for companies looking to democratize AI across their organization, bringing agility and preparedness to the business through the use of data by everyone from analysts to data scientists.

About Snowflake

Snowflakes cloud data platform shatters barriers that have prevented organizations of all sizes from unleashing the true value from their data. Thousands of customers deploy Snowflake to advance their businesses beyond what was once possible by deriving insights from their data by all their business users. Snowflake equips organizations with a single, integrated platform that offers the data warehouse built for the cloud; instant, secure and governed access to their network of data; and a core architecture to enable many types of data workloads, including a single platform for developing modern data applications. Snowflake: Data without limits. Find out more at Snowflake.com.

About NTT DATA Services

NTT DATA Services is a digital business and IT services leader. Headquartered in Plano, Texas, we are the largest division of trusted global innovator NTT DATA Corporation, a top 10 provider and part of the $109B NTT Group. With our consultative approach, we leverage deep industry expertise and leading-edge technologies powered by AI, automation and cloud to create practical and scalable solutions that contribute to society and help clients worldwide. Our global team delivers one of the industrys most robust and integrated portfolios. This includes consulting, applications, data intelligence and analytics, hybrid infrastructure, workplace, cybersecurity and business process services to help organizations accelerate and sustain value throughout their digital journeys. Visit http://www.nttdataservices.com to learn more or @NTTDATAServices.

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NTT DATA Delivers End-to-End AI Capabilities with New Data Partners, Dataiku and Snowflake - Business Wire

We are living in a time where everything is digital. Disruptive technologies like artificial intelligence (AI) has become central to this transformation. From retail to Fintech and cybersecurity to predictive analytics, tech pundits avow that AI now plays an essential cog in the future of these industries and disciplines. However, through some alarmists argue that AI is stealing jobs through automation and robotics, on the contrary, it has been observed that AI is also adding new job roles every day to the existing employment pool. Researchers have tracked down new job roles, occupations and emerging industries, in the AI landscape that can help us understand the job market better. Although the impact of AI is no longer confined to theoretical assumptions, the skillset of the existing workforce does shape the demand for jobs in this domain.

This year, the World Economic Forum had forecasted a tremendous increase in AI jobs globally over the next two years, with new jobs per 10,000 opportunities increasing from 78 today to 123 in 2022.This statistics further is backed by analyst firm Gartner, which views 2020 as a turning point where AI will start to create more jobs than it is destroying.According to a previous report, of the 1.8 million jobs AI will get rid of, the emerging field will create 2.3 million by 2020, says Gartner. Such findings, draw attention to the nexus between what is possible in the job opportunities due to AI. Economists forecast that the USA shall grow to be a major leader in AI jobs. These include machine learning engineer, data scientist, computer vision engineer and more.

According to an independent study by Poker.org, most AI jobs are being offered in states with high-population cities like California, New York, and Texas. The companys team had analyzed data from over 8,000 job advertisements, at Indeed.com in September 2020 for all 50 US states. The company also compiled online search data for AI jobs in all 50 states, adding insights by using keyword research tools to find approximate search numbers for the key terms in every state. As per the key observation, the USA state of California offered the highest jobs in AI with 1515 jobs, with San Francisco and Santa Clara offering 270 and 214 jobs respectively. Following next is Virginia with 843 jobs with Arlington having a share of 146 jobs. States like Washington, Massachusetts, New York and Texas also feature in the top 10 list, accounting for 592, 573, 562 and 447 jobs respectively. In Washington, Seattle fetches the largest share of 413 jobs, while for New Yorks New York City offered 379 jobs. Even Austin had 158 jobs opening in AI out of Texass 447 total AI-oriented jobs.

Poker.org also used Google Trends data to analyze the states where people search the most often for the term, AI Jobs. They also used keyword research tools to get a clear idea of how many times people in each state searched for that term.The top USA states searching for AI jobs the most were, California, Texas, New York, Florida and Illinois.

The AI job ads research also showed USA states with the highest number of remote jobs. The state with the most remote jobs is California (148), followed by New York (89). Texas (76), Massachusetts, (39), and Virginia (31). Furthermore, the findings revealed US states that currently offer the most entry-level jobs in AI. With California leading again (351), followed by Massachusetts (126), New York (113), Virginia (110) and Washington (84).Meanwhile, the data also showed USA states with fewest AI jobs. These are Alaska, which is also the only state with zero AI job ads, Mississippi (2) and South Dakota (4).

Brendon Thomson, a spokesperson for Poker.org, commented: Our research confirmed that AI jobs are growing fast, with thousands of new AI careers popping up around the country.

It was great to see that not all AI jobs that are currently being advertised, are mid or senior level, but there are plenty of opportunities for AI enthusiasts to join the industry through an entry-level job. The same goes for the offer of remote AI jobs in the majority of large US cities.

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Interpreting the Scope of AI job Market in the US in current times. - Analytics Insight

The Defense Innovation Board convened for its fall public meeting Tuesday and approved resolutions for two key federal technology issues in addition to broadening its work on space.

The board, which is comprised of national security technology innovators, formed a new space subcommittee to support the Space Force and heard from Michael Kratsios, acting undersecretary of defense for research and engineering, and U.S. chief technology officer.

But the need for better testing protocols for artificial intelligence systems and strategies the Defense Department could adopt in order to attract digital talent took center stage at the meeting. The board adopted resolutions after robust discussions for both issues.

Challenges in AI Testing

No proven methods for testing and evaluating nondeterministic AI systemsmeaning less predictable, more adaptable AI systemsexist. Daniela Rus, a roboticist with the Massachusetts Institute of Technology, said it is critical to have strong procedures for testing, evaluation, verification, and validation, or TEV/V, of artificial intelligence in order to create enough confidence in the technology to deploy it.

The department has been articulating the importance of accelerating the deployment of these systems, Rus said, citing DODs adoption of the boards AI ethics principles. We have seen a lot of efforts in developing AI accelerator programs that will take the latest and greatest advancements in AI from research organizations and map them into processes and procedures for the department. We hope to have these in place, but in order to get there we need to have rigorous, robust procedures for testing.

The main reason testing for these types of autonomous systems is so challenging is uncertainty. Board member Danny Hillis, a pioneer in parallel computing, said uncertainty comes in three directions: from the function, the inputs and the outputs. Hillis suggested the board should use these three areas of uncertainty to guide its thinking when it comes to providing recommendations for TEV/V.

The resolution adopted by the board argues DOD must develop its own TEV/V solutions as soon as possible, rather than wait for external solutions, in order to be ready to deploy AI systems in the short term. The boards science and technology subcommittee hopes to have two reportsone for a backgrounder and another for recommendationson TEV/V for AI by December of this year.

Without a strong push for education and training on this topic and a diverse range of testing programs at the developmental and operational levels, DoD will have difficulty assessing its current TEV/V processes and determining next steps to improve its AI TEV/V capability, the resolution reads.

Competing for Digital Talent

Later in the meeting, the DIB turned its attention to workforce issues. Jennifer Pahlka, a founder of the U.S. Digital Service and Code For America, led the groups discussion on competing for digital talent. Pahlka said the coronavirus pandemic and remote work trends could help the department attract talent if it develops new strategies to help it compete with the private sector.

As private sector remote work trends are changing how employers compete for digital talent, DOD has the opportunity to take advantage of these trends and be more competitive for civilian talent in this new environment, Pahlka said.

DOD and the federal government in general struggles to fill talent gaps for several reasons, including long hiring timelines. A recent report by the Partnership for Public Service found the average hiring timeline for the federal workforce is 98 days, or more than twice the private sector average.

The paper DIB released to accompany the discussion detailed five recommendations for what to do to attract digital talent. Overall, DOD should develop strategies to maintain a remote and distributed workforce even beyond the pandemic. Pahlka added that though the recommendations focus on attracting digital talent, she hopes the same principles outlined can be expanded across the workforce.

In the past, common wisdom said the Pentagon couldnt do mass telework. Since the onset of the coronavirus pandemic, DOD had to adapt, and fast. Lisa Hershman, the chief management officer for the Defense Department, said in July the pandemic shattered the myth DOD couldnt support remote work.

According to the DIBs report, DOD should now focus on expanding its IT infrastructure and make sure it has the tools it needs to maintain remote work as well as expand the agencys capabilities to do classified work remotely.

The report also recommends DOD work on improvements to the remote hiring process, prioritize changing the agencys culture around remote work and consider dedicated remote work pilot programs to recruit and fill critical civilian technical talent gaps at priority organizations.

The subcommittee believes the DOD is really at an inflection point for talent management, Pahlka said.

Pahlka and three other members of the DIB including former Google CEO Eric Schmidt ended their terms on the board. Member terms last four years.

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Defense Innovation Board Adopts AI Testing, Digital Workforce Recruitment Resolutions - Nextgov

Chris Cashwell

Senior Vice President of Healthcare Solutions at Digital Reasoning

NASHVILLE, Tenn., Sept. 17, 2020 (GLOBE NEWSWIRE) -- Digital Reasoning, the global leader in artificial intelligence solutions that understand human communications and behaviors, announced today that they are offering healthcare organizations Patient Intelligence at cost. Patient Intelligence is a proven AI solution that augments the cancer care workflow by identifying cancer diagnoses in real-time.

Hospitals and cancer centers could be overwhelmed by a growing backlog of cancer patients who delayed or canceled screenings, tests, treatments, or therapies during this pandemic, said Chris Cashwell, the senior vice president of healthcare solutions at Digital Reasoning. Oncology programs can quickly combine AI and their cancer teams expertise to get cancer patients treated sooner by virtually expanding capacity to increase patient volume with the same infrastructure. Unprecedented for enterprise AI software in the healthcare industry, our Solution deploys in weeks instead of months, plugs into existing diagnostic report feeds, and starts identifying cancer patients for navigation immediately.

Within the first 24 hours of deployment at Digital Reasonings newest customer last week, the AI solution identified 17 cancer diagnoses and 2 incidental lung nodules by reading through hundreds of reports in real-time. After identifying a cancer diagnosis, the AI alerts the oncology team to begin care coordination so those patients can begin treatment sooner than previously possible.

Many healthcare providers are reeling from the direct and indirect effects of COVID-19, said Tim Estes, Founder and CEO of Digital Reasoning. We looked at the situation and saw a way to help hospitals recover faster as they help patients recover. Were dispensing with business as usual. Just like when we answered our nations call after the 9/11 attacks and when we saw a need to help combat human trafficking because it was and is the right thing to do.

Hospitals, health systems, and cancer centers interested in the new, risk-free Patient Intelligence solution offer can contact Digital Reasoning at healthcare@digitalreasoning.com.

About Digital ReasoningDigital Reasoning is a global leader in understanding human communications and behavior through the combination of applied AI, deep collaboration with industry experts, and a commitment to use technology for positive change. Through the combination of our trusted technology and our customers experience, for example, patients have a better chance of surviving, banks can ensure their employees are meeting the highest standards of conduct, and law enforcement can protect the most vulnerable citizens in our society. For more information, go to http://www.digitalreasoning.com and follow on Twitter at @dreasoning.

Contact:Digital ReasoningJason Beckjason.beck@digitalreasoning.com

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/b2eb4cd3-7e58-4dd7-90c8-ca644e39e64c.

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Digital Reasoning Offers Oncology Programs Leading AI Solution at Cost Now When Health Systems and Their Cancer Patients Need Help the Most -...

SHI YU/CHINA DAILY

China's burgeoning artificial intelligence sector is urged to not to drive another round of regional development imbalance.

While on the path toward a moderately prosperous society, experts warn the AI industry should not create gaps among the affluent and poverty-stricken areas, thus affecting livelihoods in the latter.

AI industrial clusters have taken shape in the Beijing-Tianjin-Hebei and Pearl River Delta regions, but other areas are lagging behind according to a research report from the Next Generation AI Research Institute at Nankai University, released this year.

A new round of regional development imbalance is likely in the pipeline, it said.

Statistics indicate the sector is expected to see its industrial value hit 70 billion yuan ($10.3 billion), more than doubling itself from 33.9 billion yuan according to China IRN, a domestic industrial think tank.

The scale of China's core AI industry had hit 51 billion yuan by the end of 2019, with the number of AI enterprises exceeding 2,600. The figures were released at the 2020 Smart China Expo Online held in Southwest China's Chongqing municipality on Tuesday.

In order to prevent widening regional development gaps driven by the AI sector, some areas in China have undertaken trials.

For example, Tianjin, which saw its GDP tumble by one-third in late 2018, has pinned its hopes on the AI sector and doesn't expect its GDP to slide further amid the AI boom.

After three years of development, it has become a pioneer in AI city construction. It is shaping up to become a high-tech hub and has rolled out a series of supportive policies to develop industrial chains spurred by AI.

In December 2018, the city unveiled a three-year plan to boost the innovative development of seven AI-related industrial chains, including the independent and controllable information system, intelligent security, big data, advanced communications, intelligent connected vehicles, industrial robots and intelligent terminals.

It has also set up a special 10 billion yuan ($1.46 billion) fund for intelligent manufacturing and a 100 billion yuan industry fund for sectors driven by AI.

They city has an ambitious target: Building and perfecting industrial ecology for the sector, thus helping all the industries enabled by AI to see full development.

Less-developed areas in AI industries are advised to learn from Tianjin to upgrade their industrial development plans, otherwise their gaps with top AI industrial clusters will continue deepening.

Tianjin is also making efforts to curb tendencies of AI not benefiting the needy in grassroots areas.

It advised companies to join hands with community services rather than only focus their attention on high-tech industries, such as 5G, internet of vehicles, intelligent sensors and manufacturing.

For example, Teda Street, a section of Tianjin's Binhai New Area, has partnered with leading companies to build four AI systems to manage local community services including pandemic prevention, resident information, traffic and medical care.

The community's head Feng Peng told China Daily before the pandemic he was having difficulty learning about the health condition of the elderly people in the community with a population of more than 200,000, and the community was looking for a solution.

During the pandemic it found an AI-enabled telephone call survey system effective; so after the outbreak, he decided to use AI services for older adults living at home without relatives. The system sends an alert to the local central operating center if they haven't gone out for more than two days.

After the pandemic in April, 75 such families agreed to join the service.

To date, it has received 17 alerts, and community volunteers soon visited them. The community workers found the system relieved their burdens to visit the elderly every day.

Currently, many downtown Tianjin districts less developed than Binhai, are trying to use Teda's solution to help improve elderly care services for its more than 1 million people above the age of 65.

In addition, the sector should make more precise investment.

Many international AI think tanks have concluded no Chinese AI companies have been listed on the top 20 firms in the world for investment in research and development.

Gong Ke, president-elect of the World Federation of Engineering Organizations and the country's top AI expert, has said Chinese R&D funding is insufficient compared with the United States.

Due to the COVID-19 pandemic, investors' favor is shrinking, whether at home or abroad.

Future R&D investment is urged to be injected to the areas with higher profits.

We envision the AI sector should focus more of its effort on the needy, and help avoid gaps among regions and industries.

The author is chief correspondent at China Daily's Tianjin bureau.

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AI must narrow rather than widen development gaps - Chinadaily USA

PUNE, India, Sept. 17, 2020 (GLOBE NEWSWIRE) -- Data Bridge Market research released a new market study on Global AI in Fintech Market with 100+ Market Data Tables, Pie Chart, Graphs & Figures spread through its Pages and easy-to-understand detailed analysis. This Research Report spreads across 329 Pages, 53 No. of Tables, and 244 No. of Figures with summary of top companies, COVID-19 impacts and supports with tables and figures.

The AI in Fintech report acts as a thorough synopsis on the study, analysis and estimation of the market and how it is affecting this industry. The report gives current as well as upcoming technical and financial details of the industry in the forecast period. It presents a telescopic view of the competitive landscape to the client so that they can map the strategies accordingly, e.g. strategic planning supports businesses to improve and enhance their products which customers will desire to buy. The research study carried out in this global AI in Fintech market analysis report covers the local, regional as well as global markets. The company profiles of all the major market players and brands are included in the AI in Fintech report which emphasizes the moves like product launches, product enhancements, joint ventures, mergers and acquisitions and their effect on the sales, import, export, revenue and CAGR values.

AI in fintech market is expected to reach USD 9125.4 million by 2027 witnessing market growth at a rate of 65.7 % in the forecast period of 2020 to 2027. The market will witness significant growth in the years to come due to change in the technology which is developing of the business processes of financial service providers.

Download Sample Copy of the Report to understand the structure of the complete report (Including Full TOC, Table & Figures) @ https://www.databridgemarketresearch.com/request-a-sample/?dbmr=global-ai-in-fintech-market

North America is dominating the AI in Fintech Market, one of the largest and most advanced markets for AI in the world. The region has also registered the maximum adoption of AI in fintech solutions due to factors such as the strong economy, robust presence of prominent AI software and system suppliers, and the combined investment by government and private organizations for the development and growth of research & development activities.

**Although the COVID-19 pandemic continues to transform the growth of various industries, the immediate impact of the outbreak is varied. While a few industries will register a drop in demand, numerous others will continue to remain unscathed and show promising growth opportunities. Data Bridge Market Researchs in-depth research has all your needs covered as our research reports include all foreseeable market scenarios, including pre- & post-COVID-19 analysis.

These strategies help in the determination and the impact of COVID-19 on the companies and manufacturers. SWOT analysis is being used for the determination of the various segments of the market. It involves the use of the strengths, weakness, and threats which are being covered for the market. Moreover, the report also covers the various aspects of the consumers which involve the purchasing patterns, spending patterns, and geographical patterns. The impact of the pandemic on these aspects has been explained in the report. The AI in Fintech report also covers and conducts the interviews and analyses the growth of the market for the estimated growth of the market. Moreover, the impact of COVID-19 in the upcoming years has also been covered in the research study. The impacts of COVID-19 told from a statistical perspective and post Covid-19 opportunities @ https://www.databridgemarketresearch.com/covid-19-impact/global-ai-in-fintech-market

Following Top Key Players are profiled with global positioning:

Market share data is available for global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.

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Competitive landscape

**Strategies of key players and product offerings

**Potential and niche segments/regions exhibiting promising growth

**A neutral perspective towards market performance

**Must-have information for market players to sustain and enhance their market footprint

Global AI in Fintech Market: Competitive Rivalry

Analysts have also discussed the nature of the competition present in the global AI in Fintech market. Companies have been discussed at great length to ascertain the leading ones and note the emerging ones. The report also mentions the strategic initiatives taken by these companies to get ahead of the game. Analysts look at potential mergers and acquisitions that are likely to define the progress of the market in the coming years.

Market intelligence platform will help you understand:

Data Bridge Market Research employs comprehensive and iterative research methodology focused on minimizing deviance in order to provide the most accurate estimates and forecast possible. The company utilizes a combination of bottom-up and top-down approaches for segmenting and estimating quantitative aspects of the market. In addition, a recurring theme prevalent across all our research reports is data triangulation that looks at the market from three different perspectives. Critical elements of methodology employed for all our studies include:

Our market estimates and forecasts are derived through simulation models. A unique model is created customized for each study. Gathered information for market dynamics, technology landscape, application development and pricing trends is fed into the model and analyzed simultaneously. These factors are studied on a comparative basis, and their impact over the forecast period is quantified with the help of correlation, regression and time series analysis. Market forecasting is performed via a combination of economic tools, technological analysis, and industry experience and domain expertise.

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**Creating strategies for new product development

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**Supporting acquisition strategies

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Key Market Segmentation:

Vital data enclosed in the report:

Some of the Major Highlights of TOC covers:

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The AI in Fintech market report provides the following information:

**Region-wise, how will different segments behave in terms of opportunities, threats, and growth potential?

**Segments which will contribute notably to growth in Aerospace Fastener market, information on emerging opportunities

**Prominent trends and drivers and how will they contribute to market growth over the forecast period

**Players and products who would command a sizeable share of the market

AI in Fintech Market Important Factors:

What insights readers can gather from the AI in Fintech Market report?

A critical study of the AI in Fintech Market on the basis of segment 1, segment 2, segment 3 and segment 4

Learn the behaviour pattern of every AI in Fintech Market player product launches, expansions, collaborations and acquisitions in the market currently

Examine and study the progress outlook of the global AI in Fintech landscape, which includes, revenue, production & consumption and historical & forecast

Understand important drivers, restraints, opportunities, and trends (DROT Analysis)

Important trends, such as carbon footprint, R&D developments, prototype technologies, and globalization

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