TechCrunch

SEPTEMBER 2, 2021

Explosion , a company that has combined an open source machine learning library with a set of commercial developer tools, announced a $6 million Series A today on a $120 million valuation. “Fundamentally, Explosion is a software company and we build developer tools for AI and machine learning and natural language processing. .

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DevOps.com

APRIL 21, 2023

With the rapid advancement of artificial intelligence (AI) and machine learning (ML), companies need to understand and evaluate their readiness to adopt these technologies and drive material business outcomes.

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Artificial Inteligence Machine Learning Artificial Intelligence Strategy 122

The Crazy Programmer

FEBRUARY 7, 2020

We are talking about machine learning and artificial intelligence. These systems are capable of storing data and then planning strategy accordingly. On the other hand Machine Learning is the ability of machines to learn on their own without being explicitly programmed. Supervised learning.

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Artificial Inteligence Artificial Intelligence Machine Learning Knowledge Base 197

TechCrunch

JANUARY 7, 2022

The company creates optical sensors and novel classification systems based on machine learning algorithms to identify and track insects in real time. The sensor promises to provide real-time data, as well as management strategies to help farmers mitigate damage from harmful insects. The key here: real-time information.

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Machine Learning Artificial Inteligence Travel Wireless 232

CIO

SEPTEMBER 26, 2023

Monterrey region to provide Telmex value-added services The new region in Mexico, in Monterrey, is part of Oracle’s distributed cloud strategy, under which the company provides a managed open source database service available across multiple clouds for transaction processing, analytics , and machine learning workloads.

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Cloud Strategy Generative AI Data Center 361

CIO

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. It’s also used to deploy machine learning models, data streaming platforms, and databases. That’s not to say it’ll be easy.

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CIO

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

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Trends Strategy Enterprise Artificial Inteligence 363

CIO

JUNE 23, 2023

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

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Strategy Technical Review Data Software Review 290

CIO

DECEMBER 18, 2023

By Bryan Kirschner, Vice President, Strategy at DataStax For all the deserved enthusiasm about the potential of generative AI, “ ChatGPT is not your AI strategy ” remains sound advice. That is a real job that bosses can do and will enjoy doing, and it will help your strategy effort. Learn more about generative AI.

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CIO

APRIL 30, 2024

These images are then analyzed using machine learning algorithms to detect oil spills and pollutants. “A recently published patent application demonstrates this usage, describing the deployment of drones in sub-surface terrain to capture images.

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O'Reilly Media - Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. There are several known attacks against machine learning models that can lead to altered, harmful model outcomes or to exposure of sensitive training data. [8] That’s where remediation strategies come in.

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Machine Learning Artificial Inteligence Technical Review Analysis 191

Openxcell

MARCH 23, 2023

But with technological progress, machines also evolved their competency to learn from experiences. This buzz about Artificial Intelligence and Machine Learning must have amused an average person. But knowingly or unknowingly, directly or indirectly, we are using Machine Learning in our real lives.

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Artificial Inteligence Machine Learning Examples Artificial Intelligence 98

Netflix Tech

NOVEMBER 11, 2022

By Vi Iyengar , Keila Fong , Hossein Taghavi , Andy Yao , Kelli Griggs , Boris Chen , Cristina Segalin , Apurva Kansara , Grace Tang , Billur Engin , Amir Ziai , James Ray , Jonathan Solorzano-Hamilton Welcome to the first post in our multi-part series on how Netflix is developing and using machine learning (ML) to help creators make better media?—?from

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Machine Learning Artificial Inteligence Media Video 95

CIO

AUGUST 7, 2023

Softchoice develops end-to-end multi-cloud strategies and helps customers migrate to the cloud, optimize their tech stack, and modernize their operations. Softchoice’s strategies align perfectly with VMware’s portfolio and innovative solutions,” Swadish says. “We’re exclusively focused on driving the right results for customers.”

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Strategy Cloud Disaster Recovery Data Center 243

Netflix Tech

NOVEMBER 11, 2022

Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. We present a systematic overview of the unexpected streaming behaviors together with a set of model-based and data-driven anomaly detection strategies to identify them.

Machine Learning 124

Machine Learning Artificial Inteligence Metrics Training 124

CIO

DECEMBER 13, 2022

This post summarizes our conversation and describes some strategies we discussed to derive and demonstrate data analytics program value. Lucas Lau, Senior Director – Machine Learning & AI Practice Leader at Protiviti, outlined a list of categories to simplify metrics. Analytics, Business Intelligence.

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Analytics Strategy Data Metrics 264

Hacker Earth Developers Blog

DECEMBER 26, 2018

According to the Global Banking Outlook 2018 study conducted by Ernst & Young, 60-80% of the banks are planning to increase investment in data and analytics and 40-60% plan to increase investment in machine learning. Analytics and machine learning on their own are mere buzzwords. Business-driven data strategy.

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Machine Learning Artificial Inteligence Banking Analytics 202

N2Growth Blog

APRIL 25, 2024

Today’s COO wears many hats and is instrumental in executing corporate strategy, fostering innovation, driving technological integration, and steering the company toward its goals with insightful leadership. Thus, empathy and inclusive leadership have emerged as indispensable traits in the modern COO’s repertoire.

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Artificial Inteligence Strategy Recruiting Artificial Intelligence 86

Mentormate

DECEMBER 12, 2023

In a previous blog post, we introduced a five-phase framework to plan out Artificial Intelligence (AI) and Machine Learning (ML) initiatives. The Traditional Machine Learning Workflow Initiating a traditional ML project begins with collecting data. How does this help us in practice?

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Dataiku

APRIL 10, 2023

The process of converting a trained machine learning (ML) model into actual large-scale business and operational impact (known as operationalization) is one that can only happen once model deployment takes place.

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Machine Learning Artificial Inteligence Training Testing 52

Altexsoft

JUNE 29, 2021

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.

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Artificial Inteligence Machine Learning Engineering Data Engineering 105

DataRobot

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices.

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Machine Learning Artificial Inteligence Marketing Data 87

TechCrunch

DECEMBER 21, 2022

Today, technologies such as artificial intelligence (AI) and machine learning (ML) are being applied across multiple departments and are helping teams work in synergy at a faster pace. So, I’ve put together three main strategies to put you on the path to fully digitizing your business and noticeably improve the closing process.

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CIO

AUGUST 23, 2023

Having joined its executive team 18 months ago, CDIO Jennifer Hartsock oversees its global technology portfolio, and digital and data strategies, so she has to keep track of a lot of moving parts, both large and small, to help achieve the company’s big corporate strategy about being ‘better together.’ “It

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DevOps.com

MAY 10, 2024

These four machine-learning algorithms can make a real difference. Despite the hype, AI can benefit actual DevOps workflows.

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DevOps Machine Learning Artificial Inteligence Strategy 92

CIO

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. It’s a powerful strategy.” The rest are on premises. That’s really valuable.”

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CIO

JULY 31, 2022

But most importantly, without strong connectivity, businesses can’t take advantage of the newest advancements in technology such as hybrid multi-cloud architecture, Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML) and edge micro data centre deployment.

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O'Reilly Media - Data

JUNE 5, 2018

Today, just 15% of enterprises are using machine learning, but double that number already have it on their roadmaps for the upcoming year. However, in talking with CEOs looking to implement machine learning in their organizations, there seems to be a common problem in moving machine learning from science to production.

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Artificial Inteligence Machine Learning Software Review Weak Development Team 160

Datavail

MARCH 8, 2022

were unsuccessful in fulfilling their aspirations of implementing Machine Learning (ML) systems in 2021. A ML data model provides users with one of three distinct ML strategies , each of which provides a specific type of business intelligence: descriptive, predictive, and prescriptive. Datavail is here to help. Why Embrace ML?

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Machine Learning Artificial Inteligence Compliance Programming 97

CIO

APRIL 12, 2023

Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. As scope increases, so does the need for broad alignment The growth of real-time AI in the organization impacts execution strategy.

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Artificial Inteligence Artificial Intelligence Machine Learning Agile 363

InfoBest

MAY 29, 2023

In an era reminiscent of science fiction, two groundbreaking technologies have emerged, poised to reshape our world: the Internet of Things (IoT) and Machine Learning. Machine learning algorithms excel at analyzing this data, identifying patterns, and extracting valuable information.

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Artificial Inteligence Machine Learning IoT Energy 52

CIO

MAY 15, 2024

Break out with leverage, knowledge, and lighthouse strategies This is in part because we do see some companies signaling big moves beyond “use case limbo.” Verizon’s CEO is organizing genAI strategy using three buckets: “optimizing processes, product experiences, and revenue growth.” This applies in spades to genAI and “use case limbo.”

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CIO

JULY 11, 2023

Bryan Kirschner, Vice President, Strategy at DataStax Ignoring the potential of generative AI to increase productivity is a surefire way to fall behind as an individual, a team, and an organization. The most powerful framework I’ve found for effective strategic thinking is what Roger Martin calls the “strategy choice cascade.”

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Generative AI Strategy Weak Development Team Hotels 189

CIO

SEPTEMBER 2, 2022

At the centre of these changes are disruptive technologies like artificial intelligence, cloud computing, and machine learning, which are paving the way for new business models. One example is Banking-as-a-Service, with the market expected to reach US$3.6 trillion by 2030. Refining the balancing act of innovation and risk.

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Banking Innovation Strategy Artificial Inteligence 246

CIO

AUGUST 28, 2022

At the centre of these changes are disruptive technologies like artificial intelligence, cloud computing, and machine learning, which are paving the way for new business models. One example is Banking-as-a-Service, with the market expected to reach US$3.6 trillion by 2030. Refining the balancing act of innovation and risk.

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