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AI Eye Episode 391: Halliburton (NYSE: $HAL) Enters Five-Year Agreement with Accenture (NYSE: $ACN), Microsoft (NasdaqGS: $MSFT) for Digital Advancement

Veritone (NasdaqGM: $VERI) Sees Rapid Adoption of AI-Enabled Public Safety Solutions


Point Roberts, WA and Vancouver, BC - July 17, 2020 ( Newswire) (, a global investor news source covering Artificial Intelligence (AI) brings you today's edition of The AI Eye - watching stock news, deal tracker and advancements in artificial intelligence.

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AI Eye Episode 391: Halliburton (NYSE: $HAL) Enters Five-Year Agreement with Accenture (NYSE: $ACN), Microsoft (NasdaqGS: $MSFT) for Digital Advancement


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Today's Column - The AI Eye - Watching stock news, deal tracker and advancements in artificial intelligence

Stocks discussed: (NYSE:HAL) (NYSE:ACN) (NasdaqGS:MSFT) (NasdaqGM:VERI)

Halliburton (NYSE:HAL) has entered into a five-year strategic agreement with Accenture (NYSE:ACN) and Microsoft (NasdaqGS:MSFT) with the aim of advancing its digital capabilities in Microsoft Azure. According to the press release, this will complete Halliburton's move to "cloud-based digital platforms," and implement improvements such as: "enhancing real-time platforms for expanded remote operations, and improving analytics capability with the Halliburton Data Lake utilizing machine learning and artificial intelligence." Jeff Miller, Halliburton chairman, president & CEO, explained:

"The strategic agreement with Microsoft and Accenture is an important step in our adoption of new technology and applications to enhance our digital capabilities, drive additional business agility and reduce capital expenditures. We are excited about the benefits our customers and employees will realize through this agreement, and the opportunity to further leverage our open architecture approach to software delivery."

Veritone, Inc. (NasdaqGM:VERI) is experiencing rapid adoption of its AI-enabled public safety solutions. The company's AI-enabled suite of solutions have seen "a swell of adoption in 2020," with sign-ups in the first half of this year exceeding all of 2019, according to the press release. Jon Gacek, Head of Government, Legal and Compliance at Veritone, said:

"Audio and video evidence collected from crime scenes has become essential to police departments, but presents a significant challenge when it comes to reviewing and processing these large data sets. Veritone's government solutions enable police departments to process and search any media type to extract actionable intelligence quickly and easily, significantly enhancing agencies' transparency. We're excited to be partnering with more agencies than ever before, and are looking forward to a strong year of innovation in 2020."

Global Machine Learning Market to Reach $117.19 Billion by 2027

A report from Fortune Business Insights finds that the global Machine Learning market will grow from $8.43 billion in 2019 to $117.19 billion by 2027 with a compound annual growth rate (CAGR) of 39.2 percent in the forecast period 2020-2027. An excerpt from the report summary outlines the role of self-driving cars in the market's growth:

Self-driving cars have gained tremendous popularity in the recent years. The advancements in artificial intelligence technology and the Internet of Things (IoT) have paved [the] way for driverless cars. ML is a vital component of the centralized electronic control unit (ECU) in a self-driving car. Real-time monitoring of the surroundings and predicting possible changes in the environment are the primary functions of ML algorithms in self-driving cars.

ML algorithms such as supervised learning, unsupervised learning, pattern recognition algorithms, decision matrix algorithms, among others are integrated into the functioning of self-driving cars. For example, Waymo LLC, an autonomous driving technology development company headquartered in California, uses categorical machine intelligence technology to classify and detect different types of road features and objects. By incorporating advanced ML algorithms, the company intends to expand to more cities to encounter new scenarios and objects. These factors are likely to fuel the demand for intelligent retrieval algorithms, thereby aiding to the expansion of the market.

Sam Mowers,

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