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Tecton raises $100M, proving that the MLOps market is still hot

TechCrunch

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. Del Balso says it’ll be used to scale Tecton’s engineering and go-to-market teams. “We

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Data collection and data markets in the age of privacy and machine learning

O'Reilly Media - Data

In this short talk, I describe some interesting trends in how data is valued, collected, and shared. Economic value of data. It’s no secret that companies place a lot of value on data and the data pipelines that produce key features. But if data is precious, how do we go about estimating its value?

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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. Shorter time to market of ML models.

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Managing Machine Learning Workloads Using Kubeflow on AWS with D2iQ Kaptain

d2iq

Complexity: There are lots of cloud-native and AI/ML tools on the market. Security: Data privacy and security are often afterthoughts during the process of model creation but are critical in production.

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Here’s where MLOps is accelerating enterprise AI adoption

TechCrunch

Ashish Kakran , principal at Thomvest Ventures , is a product manager/engineer turned investor who enjoys supporting founders with a balance of technical know-how, customer insights, empathy with challenges and market knowledge. In the early 2000s, most business-critical software was hosted on privately run data centers.

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10 most in-demand generative AI skills

CIO

Upwork analyzed data from its platform, examining the types of projects companies hired freelancers for thus far this year, to identify the most sought-after AI skills on the market. Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer.

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Mage aims to be the ‘Stripe for AI;’ raises $6.3M for developer tools to build AI into apps

TechCrunch

“We worked with hundreds of developers who had great machine learning tools and internal systems to launch models, but there were not many who knew how to use the tools,” Dang told TechCrunch. They didn’t work with machine learning extensively, so we decided to build tools for technical non-experts.