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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

Although the principles discussed are applicable across various industries, we use an automotive parts retailer as our primary example throughout this post. An automotive retailer might use inventory management APIs to track stock levels and catalog APIs for vehicle compatibility and specifications.

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Helm.ai snags $31M to scale its ‘unsupervised’ autonomous driving software

TechCrunch

Helm.ai, a startup developing software designed for advanced driver assistance systems, autonomous driving and robotics, is one of them. says it has developed software that can skip those steps, which expedites the timeline and reduces costs; that lower cost also makes it particularly useful for advanced driver assistance systems.

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EvolutionIQ secures $21M to streamline insurance claims processing with AI

TechCrunch

And in 2016, he joined Waymo, Google parent company Alphabet’s autonomous car division, as a machine learning engineer. “While adoption of AI in a traditional industry can be challenging, [it can be] overcome by building ‘explainable AI’ systems in tight collaboration with the users,” Vykruta said.

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PQShield raises $20M for its quantum-ready, future-proof cryptographic security solutions

TechCrunch

If machine learning is shaping up to be one of the more popular (and perhaps most obvious) applications for quantum computing, security is perhaps that theme’s most ominous leitmotif. Other sectors it’s working with include automotive OEM, industrial IoT, and technology consulting, it says.).

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What is NLP? Natural language processing explained

CIO

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. NLP applications Machine translation is a powerful NLP application, but search is the most used.

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Applications of Artificial Intelligence (AI) in business

Hacker Earth Developers Blog

Improvement in machine learning (ML) algorithms—due to the availability of large amounts of data. Greater computing power and the rise of cloud-based services—which helps run sophisticated machine learning algorithms. There are also concerns about AI programs themselves turning against systems.

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KeepTruckin raises $190 million to invest in AI products, double R&D team to 700

TechCrunch

This kind of accuracy requires billions of ground truth data points that are trained and tested on KeepTruckin’s in-house machine learning platform, a process that is very resource-intensive.