Monthly Archives: September 2020

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

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AI in Fintech Market to Witness Massive CAGR Growth of 65.7% with Innovative Technology | Key Competitors Are IBM, Intel, Google, Samsung, Microsoft,...

International organizations and corporations are racing to develop global guidelines for the ethical use of artificial intelligence. Declarations, manifestos, and recommendations are flooding the internet. But these efforts will be futile if they fail to account for the cultural and regional contexts in which AI operates.

AI systems have repeatedly been shown to cause problems that disproportionately affect marginalized groups while benefiting a privileged few. The global AI ethics efforts under way todayof which there are dozensaim to help everyone benefit from this technology, and to prevent it from causing harm. Generally speaking, they do this by creating guidelines and principles for developers, funders, and regulators to follow. They might, for example, recommend routine internal audits or require protections for users personally identifiable information.

We believe these groups are well-intentioned and are doing worthwhile work. The AI community should, indeed, agree on a set of international definitions and concepts for ethical AI. But without more geographic representation, theyll produce a global vision for AI ethics that reflects the perspectives of people in only a few regions of the world, particularly North America and northwestern Europe.

This work is not easy or straightforward. Fairness, privacy, and bias mean different things (pdf) in different places. People also have disparate expectations of these concepts depending on their own political, social, and economic realities. The challenges and risks posed by AI also differ depending on ones locale.

If organizations working on global AI ethics fail to acknowledge this, they risk developing standards that are, at best, meaningless and ineffective across all the worlds regions. At worst, these flawed standards will lead to more AI systems and tools that perpetuate existing biases and are insensitive to local cultures.

In 2018, for example, Facebook was slow to act on misinformation spreading in Myanmar that ultimately led to human rights abuses. An assessment (pdf) paid for by the company found that this oversight was due in part to Facebooks community guidelines and content moderation policies, which failed to address the countrys political and social realities.

Theres a clear lack of regional diversity in many AI advisory boards, expert panels, and councils.

To prevent such abuses, companies working on ethical guidelines for AI-powered systems and tools need to engage users from around the world to help create appropriate standards to govern these systems. They must also be aware of how their policies apply in different contexts.

Despite the risks, theres a clear lack of regional diversity in many AI advisory boards, expert panels, and councils appointed by leading international organizations. The expert advisory group for Unicefs AI for Children project, for example, has no representatives from regions with the highest concentration of children and young adults, including the Middle East, Africa, and Asia.

Unfortunately, as it stands today, the entire field of AI ethics is at grave risk of limiting itself to languages, ideas, theories, and challenges from a handful of regionsprimarily North America, Western Europe, and East Asia.

This lack of regional diversity reflects the current concentration of AI research (pdf): 86% of papers published at AI conferences in 2018 were attributed to authors in East Asia, North America, or Europe. And fewer than 10% of references listed in AI papers published in these regions are to papers from another region. Patents are also highly concentrated: 51% of AI patents published in 2018 were attributed to North America.

Those of us working in AI ethics will do more harm than good if we allow the fields lack of geographic diversity to define our own efforts. If were not careful, we could wind up codifying AIs historic biases into guidelines that warp the technology for generations to come. We must start to prioritize voices from low- and middle-income countries (especially those in the Global South) and those from historically marginalized communities.

Advances in technology have often benefited the West while exacerbating economic inequality, political oppression, and environmental destruction elsewhere. Including non-Western countries in AI ethics is the best way to avoid repeating this pattern.

Link:

AI ethics groups are repeating one of societys classic mistakes - MIT Technology Review

Snowflake, the buzzy cloud computing company, just delivered the biggest software IPO ever by betting on a future in which all businesses increasingly rely on big data and AI to make decisions. Its stock began trading on Sept. 16 at $245 per sharemore than double the $120 price Snowflake set the day earliergiving it an opening valuation of $67.9 billion.

The startups main value proposition is that it makes it easier and cheaper for businesses to analyze data theyve shelved away on the cloudincluding the massive datasets needed to train machine learning algorithms. Because Snowflake structures its software differently, it can run resource-intensive AI programs more efficiently than its competitors, including juggernauts like Amazons AWS and Microsofts Azure.

Snowflake is very important because they can challenge the Amazon AWS power, said Per Roman, managing partner and co-founder of investment firm GP Bullhound. Amazons cloud service controls nearly half the global market, and takes much of the web down with it whenever it experiences disruptions.

Snowflake is only able to take on a dominant, entrenched competitor like AWS because it has come up with a better solution for one problem: allowing companies to cheaply expand their reliance on AI to help them with an ever-growing set of business decisions. That is the vision Wall Street valued at roughly $70 billion today.

AI requires two key ingredients: huge troves of data and a lot of computing power. If you have both, you can monitor the performance of your business in granular detail (and in real time) to predict future conditions. Snowflake can help companies do this kind of analysis more often and at a lower cost: In July, Snowflake handled 507 million requests per day from companies looking to track key data points in real time, according to its IPO filing.

Snowflake differentiates itself from competitors like AWS through its software architecture. The company divides its massive pool of computing power into three groups: One is dedicated to storing data, another is just for analyzing that data, and the third is a brain that keeps the other two running. The system can dedicate more resources to storage or data analysis on the fly, depending on demand.

AWS offers similar services, doesnt separate data storage and analysis, which means clients effectively pay for more analytical computing power they may not use. Snowflake, by comparison, only charges clients for exactly as much storage and computing power as they need. Snowflake also makes it easier for companies to share data with clients and partners, or to buy and sell datasets on an internal marketplace.

Roman said that every company is trending towards a future in which theyll rely on cloud services to store and analyze data. All enterprises, from the largest in the world to your small mom-and-pop shop, need to migrate their computing storage and systems into the cloud, he said. Snowflakes soaring valuation suggests that investors have bought into this bet on ubiquitous AI.

But as businesses are increasingly adopting AI to inform their strategies and automate everything from resume review to ER triage, a string of high-profile scandals has made corporate executives think twice about their use of big data. Shifting public opinion, new government regulations, and the cost of compliance could change companies calculus about AIand send Snowflakes valuation drifting back down to Earth.

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Snowflake's IPO is a bet on companies using AI for everything - Quartz

The Artificial Intelligence Company Leverages Advances in Machine Learning, Computer Vision, and IoT to Create a Single System of Record for the Industry

Dashboard AI, a technology innovator in the foodservice and hospitality industry, announces its vision for a single system of record for the industry. The company leverages advances in machine learning, computer vision, and IoT to reveal insights that improve safety, efficiency, compliance, and training that create a single system of record.

The current fragmented software landscape creates an opportune time to implement a unified platform that is the system of record for critical data around business operations, safety, inventory, staffing, and productivity. saidBrian Pierce, Dashboard AI cofounder and chairman.Our Dashboard AIs stewardship of this data creates aplatform of powerthat can be used in other business software and services categories that need access to this underlying data.

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Harnessing the recent advancements in facial recognition, computer vision, sensors, and IoT, the company is building a suite of products that automate existing operational processes that are typically performed manually.Dashboard AIs machine learning algorithms are built using the companys proprietary data and training libraries designed specifically for foodservice operations.Its machine learning capabilities include first-of-its-kind inventory and usage monitoring algorithms to naturally identify food and beverage brands within the foodservice and hospitality environment, to learn, monitor, track, and measure brand usage. These applications use the companys technology to improve accuracy, efficacy, and efficiency.

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The foodservice sector has been riveted by the global pandemic and we need to leverage technology to rethink how we can optimize our operational processes and build a foundation for the future saidBrian Pierce.At Dashboard AI,weve been working on this opportunity for over a year before the pandemic hit and as a result of its impact on the industry, weve accelerated our efforts to develop and refine our solutions.

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Dashboard AI Announces Its Technology Vision for the Foodservice - AiThority

Working the stock market is a data game. Getting the best information, in a timely way, and knowing how to use it, are keys to success. So, here are some numbers to think about. According to industry market research, artificial intelligence companies and products are on the verge of explosive growth. The sector totaled some $10 billion in 2018; by 2025, the companies, products, value-added, and marketing are expected to reach over $125 billion.

You probably already are on it, even if you didnt realize. AI tech lies behind the growth of digital personal assistants like Alexa and Siri. Most online advertising and pop-ups are powered by AI systems.

All of these systems are going to improve, as engineers and developers fine-tune the coding, create new search apps, and update the underlying hardware. And those technological improvements are going to find their way into stock values. The companies that roll them out, and build on them, are going to get a share of the coming boom.

With this in mind, Wall Street analysts have tapped three lesser-known stocks as primed for gains. Theyre an interesting lot, spread across a variety of sectors, each with their own approach to artificial intelligence.

Opening up theTipRanks database, weve pulled the details on these names, to find out what makes them compelling.

Remark Holdings (MARK)

The first company on our list uses AI to power its network of subsidiaries. Remark Holdings has its hands in many baskets online retail, digital content delivery, facial recognition, and even Chinas somewhat notorious social credit system. The company is headquartered in Las Vegas, with offices in LA, Beijing, Shanghai, and Chengdu.

Remarks platform product, KanKan, is in use across China, especially in retail. The platform delivers insights on customer behavior, so that retailers can fine-tune operations and bring the right items to the sales floor at the right time. Online, KanKan offers market targeting and credit risk analysis in the fintech sector. And in the public safety niche, Remarks KanKan brings behavioral analytics to construction sites, restaurants, and roadways.

Like many emerging tech companies, Remark typically operates at a net loss. However, the scale of that loss has been declining in sequential quarters, even during the corona pandemic. EPS in the first quarter this year was (5 cents), while it improved to (4 cents) in Q2. Both of those results beat the forecast. Revenues have been growing steadily, too, from $260,000 in Q4 last year to $431,000 in Q1 this year, to $2.3 million in Q2, the most recent reported. The companys new bio-safety business, which uses AI to monitor thermal imaging products in casinos, restaurants, hotels, and medical centers and is based in the US brought in $1.1 million of that revenue.

Covering the stock for Roth Capital, 5-star analyst Darren Aftahi strikes an upbeat note in his comments on MARK.

MARK announced it has begun discussions for potential partnerships with larger global enterprise customers for AI software deployments, which could aid scale. Additionally, MARK is continuing to see healthy demand from new customers for thermal-based offerings, while current customers have also expressed interest in additional AI features, which we believe suggests MARKs solution has staying power with customers.

In line with this outlook, Aftahi rates MARK a Buy along with a $4.25 price target. This figure suggests that MARK shares have a stellar 425% upside potential from their current price of $1. (To watch Aftahis track record, click here)

Story continues

WISeKey International Holdings (WKEY)

Next on our list is WISeKey, a company in the cybersecurity industry. WKEY develops codes, crypto-algorithms, and chips necessary to the functioning of online digital security. The company does not confine itself to a single pathway; it creates secure digital identification ecosystems using AI, as well as blockchain and IoT systems. WKEYs customers include marketers, who are looking for brand protection, and financial institutions seeking secure digital systems.

Among WISeKeys key products are semiconductor chips used in secure microcontrollers and smart card readers. These chips enable AI platforms to speed up transactions while improving safety and privacy. The company is also heavily involved in online brand and digital identity protection. WKEYs AI enabled coding and algorithms power recognition software that improves security for customers needing signature or facial authentication.

WISeKey finished 1H20 with $8 million in revenues and $16 million in cash reserves, putting the company in a solid position to weather the COVID-19 pandemic.

Covering this stock for H.C. Wainwright, analyst Kevin Dede writes, "In our view, WISeKey represents an asymmetrical risk-reward opportunity heightened by what has proven to be a surprising ability to deliver a constant stream of new technology and solutions with realworld applicability, and perhaps most importantly, accordant customer relationships.

Dedes comments are optimistic, as is his Buy rating and $9 price target. This target implies implies 31% upside to the stock for the coming year. (To watch Dedes track record, click here)

Five9 (FIVN)

The last stock on todays list, Five9, is a cloud computing firm offering a scalable contact center platform based on intelligent cloud technology. With the corona virus pandemic having further pushed the ever-growing trend towards moving routine business online, Five9s services have become more important to its customers and more marketable.

The company has seen slow, steady revenue growth, which reached $99.8 million in Q2, and EPS that consistently beats the forecasts. While the company posted net losses in both Q1 and Q2, earnings in those quarters beat the estimates by 33% and 50% respectively.

Five9 uses AI tech to create a better customer contact platform. The companys products on mobile, web, chat, email, or social media streamline the agent-customer engagement, making inbound and outbound contacts more efficient for the contact center. One agent can handle each of the channels from a single desktop AI interface. The promise and more importantly, delivery of better online customer service is a gold mine in todays environment, and supports the quarterly results.

From Canaccord Genuity, 5-star analyst David Hynes sees Five9 as top-tier when it comes to technology and products.

One of several important differentiators for Five9 is the firms open platform and the best-of-breed choices that it avails to customers. In a continuation of that philosophy, Five9 has announced the availability of Voicestream, an API for streaming agent/caller audio to third-party applications in real-time. This API enables real-time, cloud-to-cloud media streaming so that developers and partners who are focused on AI and other innovative areas can integrate their applications directly into Five9s platform, Hynes opined.

Accordingly, Hynes gives FIVN shares a Buy rating, and his $145 price target suggests the stock has a 23% upside potential for the coming 12 months. (To watch Hynes track record, click here)

To find good ideas for AI stocks trading at attractive valuations, visit TipRanks Best Stocks to Buy, a newly launched tool that unites all of TipRanks equity insights.

Disclaimer: The opinions expressed in this article are solely those of the featured analysts. The content is intended to be used for informational purposes only. It is very important to do your own analysis before making any investment.

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3 Artificial intelligence Stocks to Consider as the Trend Heats Up - Yahoo Finance