Category Archives: Ai

In Brief

AI has been quietly invading our lives. From ouroperating roomsto our roads, and even our homes. Still, we never expected AI to infringe on onething in particular, our Super Smash Brothers. If you havent heard of Super Smash Brothers, do yourself a favor.

Super Smash Brothers is a popular video game series spanning multiple generations of gaming consoles. Unlike what we have seen AI do before with professional players inchess,poker, and the ancient game ofGo Super Smash Brothers is a particularly tricky game for AI.

In order to win, players must take full advantage of their environment, their character, and their enemys weaknesses. Players must be quick to weaken their enemies without taking too much damage so that they can knock their opponent off the stage, a feat demanding a proper strategy and a certain sense of ruthlessness.

So how did the AI do it? Software named Phillip was created by a Ph.D. student at MIT with the help of his friend from NYU. The pair constructed an AI that at first wasnt too great at the game, but eventually, after a week of consistent practice, the AI was able to react 6 times quicker than a normal human. Clocking in reaction times at 33 milliseconds compared to 200 milliseconds human reaction time, Phillip was in his own alternate reality in the game.

Phillip faced off against a tenured, five-year champion, named Gravy. In a harrowing match, Phillip bested him 8 5.

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AI System Finds Another Game to Dominate Humans - Futurism - Futurism

TechCrunch

Google Assistant, its AI-based personal helper, rolls out to Nougat and Marshmallow handsets TechCrunch Today, the company announced that it would be rolling out Google Assistant, its conversational search and AI-based personal helper (and answer to Apple's Siri and Amazon's Alexa), to smartphones running Google Play services on unforked versions of ... Amazon just recruited Motorola for its war with Google over the future of computingBusiness Insider Watch out Alexa: Google's AI assistant's been released into the wild at MWC integrating with Nokia, Samsung, Huawei ...City A.M. MWC 2017: Google Assistant Expands Beyond Pixel to New Android SmartphonesMac Rumors all 141 news articles »

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Google Assistant, its AI-based personal helper, rolls out to Nougat and Marshmallow handsets - TechCrunch

TechCrunch

Conversational AI and the road ahead TechCrunch In recent years, we've seen an increasing number of so-called intelligent digital assistants being introduced on various devices. At the recent CES, both Hyundai and Toyota announced new in-car assistants. Although the technology behind these ...

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Conversational AI and the road ahead - TechCrunch

Every business has customers. Every customer needs care. Thats why CRM is so critical to enterprises, but between incomplete data and clunky workflows, sales and marketing operations at most companies are less than optimal.

At the same time, companies that arent Google or Facebook dont have the billion-dollar R&D budgets to build out AI teams to take away our human efficiencies. Even companies with the right technical talent dont have the petabytes of data that the tech titans use to train cutting-edge neural network models.

Salesforce hopes to plug this AI knowledge gap with Einstein. According to chief scientistRichard Socher, Einstein is an AI layer, not a standalone product, that infuses AI features and capabilities across all the Salesforce Clouds.

The 150,000+ companies who already use Salesforce should be able to simply flip a switch and deploy AI capabilities to their organization. Organizations with data science and machine learning teams of their own can extend that base functionality through predictive APIslike Predictive Vision and Predictive Sentiment Services, which allows companies to understand how their products feature in images and video and how consumers feel about them.

The improvements are already palpable. According to Socher, Salesforce Marketing Clouds predictive audiences feature helps marketers hone in on high-value outreach as well as re-engaging users who might be in danger of unsubscribing. The technology has led to an average 25 percent lift in clicks and opens. Customers of Salesforces Sales Cloud have seen a 300 percent increase in conversions from leads to opportunities with predictive lead scoring, while customers of Commerce Cloud have seen a 7-15 percent increase in revenue per site visitor.

Achieving these results has not been cheap. Salesforces machine learning and AI buying spree includes RelateIQ ($390 million), BeyondCore ($110 million), and PredictionIO ($58 million), as well as deep learning specialist MetaMind of which Socher was previously founder and CEO / CTO. Marc Benioff spent over $4 billion to acquire the right talent and tech in 2016.

Even with all the right money and the right people, rolling out AI for enterprises is fraught with peril, due to competition and high expectations. Gartner analyst Todd Berkowitz pointed out that Einsteins capabilities were not nearly as sophisticated as standalone solutions on the market. Other critics say the technology is at least a year and a half from being fully baked.

Infer is one of those aforementioned standalone solutions offering predictive analytics for sales and marketing, putting them in direct competition with Salesforce. In a detailed article about the current AI hype, CEO Vik Singh claims that big companies like Salesforce are making machine learning feel like AWS infrastructure which wont result in sticky adoption. Singh adds that machine learning is not like AWS, which you can just spin up and magically connect to some system.

Socher acknowledges that challenges exist but believes they are surmountable.

Communication is at the core of CRM, but while computers have surpassed humans in many key computer vision tasks, natural language processing (NLP) and natural language understanding (NLU) approaches fall short of being performant in high stakes enterprise environments.

The problem with most neural network approaches is that they train models on a single task and a single data type to solve a narrow problem. Conversation, on the other hand, requires different types of functionality. You have to be able to understand social cues and the visual world, reason logically, and retrieve facts. Even the motor cortex appears to be relevant for language understanding, explains Socher. You cannot get to intelligent NLP without tackling multi-task approaches.

Thats why the Salesforce AI Research team is innovating on a joint many-task learning approach that leverages transfer learning, where a neural network applies knowledge of one domain to other domains. In theory, understanding linguistic morphology should alsoaccelerate understanding of semantics and syntax.

In practice, Socher and his deep learning research team have been able to achieve state-of-the-art results on academic benchmark tests for main entity recognition (identifying key objects, locations, and persons) and semantic similarity (identifying words and phrases that are synonyms). Their approach can solve five NLP tasks chunking, dependency parsing, semantic relatedness, textual entailment, and part of speech tagging and also builds in a character model to handle incomplete, misspelled, or unknown words.

Socher believes that AI researchers will achieve transfer learning capabilities in more comprehensive ways in 2017 and that speech recognition will be embedded in many more aspects of our lives. Right now, consumers are used to asking Siri about the weather tomorrow, but we want to enable people to ask natural questions about their own unique data.

For Salesforce Einstein, Socher is building a comprehensive Q&A system on top of multi-task learning models. To learn more about Salesforces vision for AI, you can hear Socher speak at the upcoming AI By The Bay conference in San Francisco (VentureBeat discount code VB20 for 20 percent off).

Solving difficult research problems is only step one. Whats surprising is that you may have solved a critical research problem, but operationalizing your work for customers requires so much more engineering work and talented coordination across the company, Socher reveals.

Salesforce has hundreds of thousands of customers, each with their own analyses and data, he explains. You have to solve the problem at a meta level and abstract away all the complexity of how you do it for each customer. At the same time, people want to modify and customize the functionality to predict anything they want.

Socher identifies three key phases of enterprise AI rollout: data, algorithms, and workflows. Data happens to be the first and biggest hurdle for many companies to clear. In theory, companies have the right data, but then you find the data is distributed across too many places, doesnt have the right legal structure, is unlabeled, or is simply not accessible.

Hiring top talent is also non-trivial, as computer scientists like to say. Different types of AI problems have different complexity. While some AI applications are simpler, challenges with unstructured data such as text and vision mean experts who can handle them are rare and in-demand.

The most challenging piece is the last part: workflows. Whats the point of fancy AI research if nobody uses your work? Socher emphasizes that you have to be very careful to think about how to empower users and customers with your AI features. This is very complex but very specific. Workflow integration for sales processes is very different from those for self-driving cars.

Until we invent AI that invents AI, iterating on our data, research, and operations is a never-ending job for us humans. Einstein will never be fully complete. You can always improve workflows and make them more efficient, Socher concludes.

This article appeared originally at Topbots.

Mariya Yao is the Head of R&D atTopbots, a site devoted to chatbots and AI.

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What Salesforce Einstein teaches us about enterprise AI - VentureBeat

TechCrunch

Super Smash Borg Melee: AI takes on top players of the classic ... TechCrunch You can add the cult classic Super Smash Bros Melee to the list of games soon to be dominated by AIs. Research at MIT's Computer Science and Artificial.. Machine Learning AI Demolishes World's Top Super Smash Bros ...Hot Hardware AI beats professional players at Super Smash Bros. video game ...New Scientist AI beats humanity at Nintendo's Super Smash Brothers - The InquirerThe INQUIRER all 5 news articles »

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Super Smash Borg Melee: AI takes on top players of the classic ... - TechCrunch

Artificial intelligence is no longer the sole domain of tech companies like Google, Facebook, IBM, and Amazon. Recognizing the potential of exponential technologies like AI and bots, creative agencies like Ogilvy and consulting firms like McKinsey and Accenture now proudly feature AI departments.

The message to brands executives is clear: understand and leverage trends in automation and artificial intelligence, or perish.

According to McKinseys Michael Chiu, As many as 45 percent of the activities individuals are paid to perform can be automated by adapting currently demonstrated technologies. In the United States, these activities represent about $2 trillion in annual wages. Andrew Ng, chief scientist at Baidu and Stanford professor of machine learning, puts it this way: If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.

Breakthroughs in deep learning have driven major advances in machine perception. Computers can now reliably detect and classify objects in images and video, transcribe and translate speech as well as humans, and even generate art, music, and movie soundtracks.

Above: An example of dense image captioning enabled by recent breakthroughs in computer vision. Image Credit: Stanford University, Department of Computer Science / Justin Johnson, Andrej Karpathy, Li Fei-Fei

AI companies like Clarifai, Ditto, and GumGum are leveraging these new technologies to help brands understand content, identify brand mentions, and calculate earned media spend from sponsorships. Other companies like Affinio, Motiva, and Reflektion improve marketing intelligence, automatically optimize campaigns, and streamline customers retail experiences.

Last year, Salesforce acquired an AI startup called MetaMind to integrate into Salesforce Einstein, to automate many sales, CRM, and ERP processes for your business.

The type of A.I. that appeals to investors is not necessarily the same that enterprises will buy. Investors look for 100x returns on capital, so they heavily scrutinize a founding teams technical pedigree, industry expertise, margin defensibility, and broad market potential.

On the other hand, executives dont need (or want) a lesson in computer science, they want to know how this technology can be used as a tool to help them achieve their business goals, points out Ophir Tanz, CEO of GumGum. GumGum is an applied vision company thathas partnered with Fortune 100 brands to curate visual content and optimize brand marketing since 2008.

Tanz highlights just a few of the many applications of computer vision for brands: Retailers can leverage visual search and increase revenue through shoppable imagery; sports teams and rights holders can deliver more accurate valuations of broadcast and social exposure; social media can be scoured and activated like never before.

Normally when brands sponsor major sporting or social events, they cant easily calculate the earned media lift or the ROI on their investment. GumGums vision technologies can identify when brand logos have appeared in social media images or sports videos, making such calculations possible.

While the technical expertise required to successfully strategize for and implement AI technologies for major brands may seem daunting and out of reach, partners like GumGum combine industry expertise, full-service agency services, and AI expertise to help brands ramp up.

Zachary Jean Paradis, vice president of customer experience at SapientNitro, has helped brands in industries ranging from financial services to CPG get started with their AI strategy. He emphasizes to his clients that AI is not a single thing, but rather a series of methods and technologies that allow you to mimic human intelligence. The key question to answer is what intelligence am I trying to mimic?

His recommendation to brands is to start with offerings from foundational mainstays like Google, Microsoft, IBM, and Salesforce and then layer in specific vendors, such as Cycorp and Luminoso, for natural language understanding or Clarifai and Sentient for computer vision. In many cases, brands can minimize the amount of bespoke code they need to write.

As transformative as AI is for many industries, the technology is not magic. One mistake non-technical brand executives make is to assume that artificial intelligence is some kind of silver bullet, according to Ryan Detert, CEO of Influential. Some executives think AI is a sentient being, like in Terminator. They ask if it can think and tell them what to do. We have to explain that AI is simply a better way to turn data into actionable insights.

Such misconceptions are not necessarily the fault of the executives. Many startups capitalize on the knowledge gap in AI to hype up marketing fluff such as executive brains that can predict the future and automatically increase revenue. No wonder executives are confused aboutwhat AI can and cannot do.

Detert and his team help brands improve the performance of sponsored social media posts by matching campaign and brand content to the right influencers based on personality, context, and timing. Normally, sponsored posts by influencers suffer from a 20 to 30 percent drop in engagement rates. By leveraging AI powered by IBM Watson, Influential is able to instead drive gains of 20 to 30 percent across ad recall, positive sentiment, social engagement, clickthrough rates, and ROI. The key industries thatbenefit from this targeted influencer marketing are consumer product goods (CPG) and entertainment businesses.

Its not that hard fordevelopers to leverage Watsons cognitive services, but non-technical teams without the requisite software development, data science, or machine learning capabilities are often mystified by the process. Due to lag of time and the ever-moving landscape, most corporate companies move slowly, Detert notes.

In the cost-benefit analysis of whether to build or buy, enterprises typically move faster with an experienced vendor or consultant. After all, if McKinsey has to write guides to teach executives the basics of software development, perhaps fast-moving technology projects are best managed by experts.

Building competitive AI from the ground up requires expensive specialized talent and volumes of proprietary structured data. Luckily for most brands, this is not yet necessary.

Many brands, like Disney, Uniqlo, and the New York Times, have successfully experimented with chatbots on Facebook, Slack, or Kik, while others have dipped their toe into voice-based technologies by releasing Alexa Skills for the Amazon Echo.

Paradis of SapientNitro points out that plenty of chatbot enablers exist, includingIBM Watson, Nuance, Microsoft Bot Framework, Googles API.ai, and Facebooks Wit.ai.

While the tech industry does not perceive brand usage of mainstay vendors as real AI, such experiments nevertheless solve important business problems and are essential for executives to stay educated and competitive in digital.

In the liquor and spirits industry, companies are legally required to put up an age gate to protect minors from digital content. No matter how much you optimize the birth date input form, manual input by users leads to massive drop-off rates, particularly on mobile.

Above: Allowing consumers to input birth dates via voice improves conversion rates for CPG companies like Anheuser-Busch.

Thats why Anheuser-Busch, the worlds largest beer producer and the company behind Budweiser, implemented a voice input option alongside the regular form. In testing, these new designs improved the consumer experience and conversion rates. In development, the technology needed to proactively handle misspoken or misunderstood words while also equating December 23rd 1994 to 23rd of December 1994 and many other permutations.

According to Lucas Herscovici, vice president of consumer connections of Anheuser-Busch, the company was able to go from idea to implementation in less than 3 months. The bulk of the time was spent validating with legal and compliance and negotiating with vendors, while the actual technical integration took less than 3 weeks.

By corporate standards, thats a fast turnaround time.

When we first introduced websites, they were a train-wreck. They didnt work well technically or design-wise, Paradis reminds us. Similarly, AI is in a young adult, awkward teenage phase. Some technologies will do very well out of the box, some will be a challenge.

From C-suite executives to front-line managers, business leaders will need to identify where AI can and cannot make an organizational impact and continuously prototype, prototype, prototype in order to raise their AI IQ, in Paradis words.

McKinsey estimates that the benefits of implementing the right automation and AI technologies can be 3 to 10 times the cost. Thus, the ability to staff, manage, and lead increasingly automated organizations will become an important competitive differentiator.

As with any technology wave, there are leaders and laggards in AI. Paradis of SapientNitro observes that the single industry thats leading end-to-end is financial services. Companies hes worked with in the space are leveraging AI and bot technologies for customer engagement, process automation, fraud and risk mitigation, business analysis, and improved executive decision making.

Not all industries have seen the same benefit. In telecom, weve seen the introduction of chatbots, but they didnt perform to the level that was expected, Paradis says. Similarly, he sees challenges for consumer packaged goods (CPG) and quick-service restaurants (QSR).

CPG brands are challenged not just by AI, but by competing in an era driven by customer experience when they dont own many of the customer touch points. Many of them own the marketing experience, but not the retail experience, which means they are missing critical purchasing behavior about their products. At the same time, many retailers are introducing private label products that are directly competitive.

CPG products are also generally too simple to turn into connected products. Adding sensors or Bluetooth connectivity would make their products prohibitively expensive without adding much utility for consumers. While companies like Google and Facebook generate petabytes of data from their consumers every move, CPG companies are in the dark with consumer usage data.

AI can still be used by CPG companies to improve marketing insights and strengthen product innovation pipelines, but the data gaps across the industry make application of data and AI very limited, says Paradis.

The same applies to QSRs, which have historically been slow to collect the requisite data to power AI initiatives. Many QSRs such as McDonalds are cash-driven businesses, making consumer purchasing trends harder to track.

Self-service kiosks can close inefficiencies and reduce costs, but AI will not cost-cut you into leadership, warns Paradis. Instead, companies need to radically rethink how AI can free up humans to deliver on the highest value activities.

The majority of sales of McDonalds in Europe go through a kiosk. Theres only a single pay register, Paradis says. But there are hosts and hostesses to welcome you at the door, walk you to the kiosks, explain your menu options, and bus your table. Instead of eliminating humans, McDonalds can deliver a more amazing experience.

This article appeared originally at Topbots.

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Common misconceptions brand executives have about AI - VentureBeat

Like wood stacking up behind an arrowhead, Salesforce, Microsoft, Google and other tech titans are gathering behind artificial intelligence, or AI. More importantly, line-of-business executives (LOBs), the new shot-callers in tech, now expectAI to deliver real-world results, particularly in the contact center.

All of this means tectonic change is coming, and just about everyone better brace for the impact.

The contact center and other operations touching the customer are emerging as the sweet spots for AI in the enterprise. In a Forrester survey, 57 percent of AI adopters said improving the customer experience is the biggest benefit. Marketing and sales, product management, and customer support lead the AI charge.

In February, Salesforce unveiled Einstein AI for its Service Cloud contact center offering. Customer service agents will lean on Einstein AI to give them information about a particular customer when they need it, as well as escalating cases using machine learning. Managers will tap Einstein AI for insights about their contact center operations, in order to make changes and boost customer satisfaction scores.

AI in the contact center isnt new. At Dreamforce last year, Humana, a healthcare insurance company, showcased its use of AI for listening to customers in the contact center and flagging elevated tones. In turn, the AI bot Cogito informs the customer service agent to change tactics.

Related:Zero One: Are You Ready for AI?

Best use cases for deep learning and AI occur in contact centers with lots of historical customer service data, such as email transcripts and chat logs, said Mikhail Naumov, co-founder and president of DigitalGenius, an AI tech company. Contact centers dealing with lots of repetitive questions are also ripe for AI.

Microsoft, too, is driving AI into its core products, from Cortana Intelligence Suite to Dynamics 365. Speaking atChannel Visionariesin San Jose, Calif., in January, Larry Persaud, director of Azure strategy, gave an example of an AI chatbot helping an agent lock in a hotel reservation. Microsofts AI technology also improves the Uber customer experience by ensuring drivers match their profile photos and securing passenger information.

We want our partners to understand what this really means for the future [and] to learn about the business and technical aspects, Persaud said. Data and intelligence are very tightly coupled. Were adding machine learning aspects, readying AI into our data platform.

Related:Zero One: Can the Channel Pivot to Digital Business in the Cloud?

Theres no question AI tremors will be felt across the channel landscape.

My bet is well see huge progress in the next 12 months, said Tim Fitzgerald, vice president of digital transformation at Avnet Technology Solutions. It will impact substantially the as-a-service commerce, transaction experience and the ability to support localization and personalization on a specific customer level.

Echoing Microsoft, Googles Sergey Brin, speaking at theWorld Economic Forum Annual Meetingin Davos-Klosters, Switzerland, in January, said Googles AI technology called Google Brain probably touches every single one of our main projects, ranging from search to photos to ads to everything we do.

As major platform vendors embrace AI, particularly in the contact center, its important to maintain a little perspective, said Forrester analyst Ian Jacobs.

Todays AI chatbots in the contact center are good at basic tasks, such as delivering content, replenishing a pre-paid phone account, and handling information requests that require accessing a single knowledge source, Jacobs said. Complex problems, such as troubleshooting a router and reconnecting a smart thermostat to it, still require human agents.

In other words, LOBs shouldnt expect AI to replace legions of human agents and, in the process, bring about massive savings.

Using AI for basic blocking and tackling, rather than for moonshot projects, means brands will see tangible results much sooner, even if those results are somewhat more modest, Jacobs said.

Tom Kaneshige writes the Zero One blog, covering digital transformation, big data, AI, marketing tech and the Internet of Things for line-of-business executives. He is based in Silicon Valley. You can reach him attom.kaneshige@penton.com.

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Zero One: AI Transforms the Contact Center - MSPmentor

In many ways, the tech worlds AI arms race is really a fight for talent. Skilled engineers are in short supply, and Silicon Valleys biggest companies are competing to nab the best minds from academia and rival firms. Which is why it makes sense that Apple has announced its expanding its offices in Seattle, where much of its AI and machine learning work is done.

Seattle is home not only to the University of Washington and its renowned computer science department, but also the Allen Institute for Artificial Intelligence. Microsoft and Amazon are headquartered nearby, and AI startups are finding a home in the region, too. Last August, Apple even bought a Seattle-based machine learning and artificial intelligence startup named Turi for an estimated $200 million, and the team is said to be moving into Apples offices at Two Union Square as part of the expansion.

Carlos Guestrin, a University of Washington professor, former Turi CEO, and now director of machine learning at Apple, told GeekWire: Theres a great opportunity for AI in Seattle.

Guesterin said Apples Seattle engineers would be looking at both long-term and near-term AI research, developing new features for the companys products across the whole spectrum. He added: Were trying to find the best people who are excited about AI and machine learning excited about research and thinking long term but also bringing those ideas into products that impact and delight our customers.

As part of the news, the University of Washington also announced a $1 million endowed professorship in AI and machine learning named after Guesterin. Thats one way to give back to the AI community.

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Apple is expanding its Seattle offices to focus on AI and machine learning - The Verge

The News Journal Published 11:23 a.m. ET Feb. 24, 2017 | Updated 5 hours ago

Red Clay School District has upheld a decision by A.I. du Pont High School Principal to remove the boys basketball team from consideration for the upcoming DIAA state tournament. 2/24/17 Damian Giletto/The News Journal

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DMA's commandant, Anthony Pullella, responds to accusations his students provoked an incident between A.I. players and fans during a basketball game last week. 2/24/17 JOHN J. JANKOWSKI JR./SPECIAL TO THE NEWS JOURNAL

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Red Clay Consolidated School District will review a decision by the A.I. du Pont High School principal to ban the boys basketball team from participating in the upcoming DIAA Boys Basketball Tournament. 2/23/17 Damian Giletto/The News Journal

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Red Clay upholds A.I. principal's decision to end season

DMA commandant responds to incident at A.I. basketball game

A.I. du Pont principal, parents meet over basketball suspensions

A.I. duPont High School principal Kevin Palladinetti tries to answer questions from parents and political leaders about an incident after the team's 58-46 loss at Delaware Military Academy last Thursday that lead the team from participating in the upcoming DIAA Boys Basketball Tournament.(Photo: Jennifer Corbett, The News Journal )Buy Photo

Red Clay Consolidated School District has upheld a decision by A.I. du Pont High School Principal KevinPalladinetti to remove the boys basketball team from consideration for the upcoming DIAA state tournament.

"We understand it was a difficult decision by staff at A.I. High School but we support that decision and stand behind it, said Superintendent Merv Daugherty. The district believes the disciplinary consequence fits the seriousness of the incident.

Jen Field, whose son is a senior on the team, told The News Journal that a group of those opposed toPalladinetti's decision will meet Friday night to discuss what, if any, next steps they will take.

Palladinettis decision stemmed from an incident following the Tigers loss at Delaware Military Academy on Feb. 16.

With 40 seconds left, an A.I. player was given a technical foul. At that point, A.I. head coach Tom Tabb said he told the players on the bench to skip the customary postgame handshake line. Instead, the coach told the team he would shake hands with the DMA team, and the players were to remain behind him and follow him off the court as a group.

When the game was over, a player started to walk and then sprinted, which caused a chain reaction where the other players followed, the coaches followed, parents followed, some DMA parents followed, Tabb said Thursday.

RELATED: More on the incident and reaction

FOOTBALL: Middletown product eyes NFL

Officials from both schools said the A.I. players ran toward a stairwell leading to thesecond level of the gymnasium, whereDMA students and fans had been watching the game.

DMA officials said they blocked the players from accessing the mezzanine while another teacher directed DMA students out through an emergency door.

Several parents of A.I. du Pont players have alleged that racial slurs were spoken by DMA players, fans and students during the game. But Palladinetti said Tabb, Assistant Principal Damon Saunders (both of whom are black)and the other A.I. assistant coaches did not report hearing any racial slurs.

DMA Commandant Anthony Pullella was at the game and said he did not hear any racial comments. Michael Ryan, the athletic director, said DMA officials conducted their own investigation, questioning parents, players, coaches and fans. He said no evidence was uncovered about any racial comment being used.

In a statement issued Friday, Red Clay officials said the district will also "continue to work with DMA to investigate allegations of inappropriate actions by their players and fans. The district has requested that DMA administration investigate from their school. Red Clay also requested a formal investigation from DIAA about the conduct of the fans during the AIHS/DMA game. We will share all investigative findings concerning fan conduct when we receive them from DMA and DIAA."

The district is taking the claims of inappropriate behavior from game attendees very seriously, Daugherty said. We do not condone the behavior in any way and will continue to work closely with DMA to uncover any acts of impropriety.

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School district upholds decision; AI's season over - The News Journal

Forbes

AI Predicts Autism By Comparing Babies' Brains Forbes Diagnosing autism spectrum disorder in children is difficult, but that info can give families a wealth of new support options, not to mention a helpful new perspective. Thanks to some infant-focused AI, doctors may soon be able to reach that diagnosis ... and more »

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AI Predicts Autism By Comparing Babies' Brains - Forbes