CIO
JULY 28, 2022
That is backed up by a 2021 survey by industry analysts at Forrester, which showed that, of 2,329 data and analytics decision-makers worldwide, 55% want to hire data scientists. And machine learning engineers are being hired to design and build automated predictive models. More advanced companies get that.
d2iq
FEBRUARY 19, 2021
Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.
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TechCrunch
MAY 10, 2022
“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .
TechCrunch
AUGUST 17, 2021
Less than a year after its $3 million seed round, San Francisco- and Africa-based fintech Pngme has snapped up another $15 million for its financial data infrastructure play. The company is also describing itself as a machine learning-as-a-service platform. Pngme will use the investment to acquire more customers, it says.
TechCrunch
JANUARY 10, 2023
Observability tools to capture and analyze IT tool data aren’t new — and these days, they’re raising a respectable amount of capital. Monte Carlo , whose platform uses machine learning to infer what data looks like and assess its impact, became a unicorn last May with $135 million in funding.
TechCrunch
OCTOBER 7, 2021
Increasingly, conversations about big data, machine learning and artificial intelligence are going hand-in-hand with conversations about privacy and data protection. They could see that the longer-term issue would be a growing need and priority for data privacy. But humans are not meant to be mined.”
CIO
FEBRUARY 13, 2023
CIOs anticipate an increased focus on cybersecurity (70%), data analysis (55%), data privacy (55%), AI/machine learning (55%), and customer experience (53%). Here is a look at five hot technology investments CIOs and other IT leaders are making in 2023 and two that have grown cold.
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