TechCrunch
AUGUST 25, 2021
Meet Taktile , a new startup that is working on a machine learning platform for financial services companies. This isn’t the first company that wants to leverage machine learning for financial products. They could use that data to train new models and roll out machine learning applications.
TechCrunch
NOVEMBER 16, 2021
Machine learning is exploding, and so are the number of models out there for developers to choose from. million seed round from Unshackled Ventures, Kepler Ventures, On Deck, Basecamp Fund, Abstraction Capital, Unpopular Ventures, Darling Ventures and a number of industry angels. Today, the early-stage startup announced a $1.64
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CIO
NOVEMBER 14, 2024
The data and AI industries are constantly evolving, and it’s been several years full of innovation. Data scientists and AI engineers have so many variables to consider across the machine learning (ML) lifecycle to prevent models from degrading over time.
TechCrunch
JANUARY 3, 2024
Satellite imagery and machine learning offer a new, far more detailed look at the maritime industry, specifically the number and activities of fishing and transport ships at sea. Turns out there are way more of them than publicly available data would suggest, a fact that policymakers should heed.
Advertiser: Data Robot
Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations.
CIO
NOVEMBER 18, 2024
In the quest to reach the full potential of artificial intelligence (AI) and machine learning (ML), there’s no substitute for readily accessible, high-quality data. By partnering with industry leaders, businesses can acquire the resources needed for efficient data discovery, multi-environment management, and strong data protection.
TechCrunch
NOVEMBER 14, 2021
In that Economist report, I spoke about society entering an “Industrial Revolution of Data,” which kicked off with the excitement around Big Data and continues into our current era of data-driven AI. What we saw over the horizon was an even bigger wave of machine-generated data. Yet, full automation evades the industry.
Advertiser: Data Robot
Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations.
Advertiser: Data Robot
As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.
Advertiser: Data Robot
The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.
Advertiser: Data Robot
More and more critical decisions are automated through machine learning models, determining the future of a business or making life-altering decisions for real people. These failures can also significantly erode human trust in AI, rendering it ineffective for real-world applications in many industries. AI is becoming ubiquitous.
Advertiser: Data Robot
While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? Renowned author and professor Tom Davenport conducted an in-depth study (sponsored by DataRobot) on how organizations have become AI-driven using automated machine learning.
Speaker: Rob De Feo, Startup Advocate at Amazon Web Services
Machine learning techniques are being applied to every industry, leveraging an increasing amount of data and ever faster compute. But that doesn’t mean machine learning techniques are a perfect fit for every situation (yet). In what new directions machine learning’s most advanced practitioners are taking it now.
Speaker: Paul Weald, Contact Center Innovator
Learn how to streamline productivity and efficiency across your organization with machine learning and artificial intelligence! How you can leverage innovations in technology and machine learning to improve your customer experience and bottom line. November 10th, 2022 at 11:00 am PST, 2:00 pm EST, 7:00 pm GMT
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