Topic: ai

SD Times news digest: Google Play feedback, Uno Platform 3.0 released, and IBM’s Call for Code global challenge finalists

Google shared its full perspective on supporting developers’ ability to choose how they distribute their apps through multiple app stores on different platforms, ensuring equal treatment for all apps, and allowing developers to communicate with customers. The company explained it will be making changes in Android 12 next year to make it easier for people … continue reading

The Future of Testing is AI: Visual AI

Applications and the environments they live in continue to become more complex. While shift-left testing helps improve app quality, alone it’s not enough to ensure quality as new frameworks and tools emerge. With Applitools AI-powered visual testing and monitoring platform, leading companies are improving app quality, accelerating delivery cycles and reducing the time it takes … continue reading

GPT-3: Advancing the understanding of cues for coding, writing

OpenAI says it is backlogged with a waitlist of prospective testers seeking to assess if the first private beta of its GPT-3 natural language programming (NLP) tool really can push the boundaries of artificial intelligence (AI). Since making the GPT-3 beta available in June as an API to those who go through OpenAI’s vetting process, … continue reading

Microsoft announces it will exclusively license OpenAI’s GPT-3 language model

Microsoft has revealed it is teaming up with OpenAI to exclusively license GPT-3. According to the company, this will further Microsoft’s goals to develop and deliver advanced AI solutions for customers, as well as create new solutions that harness the power of advanced natural language generation. GPT-3 is an autoregressive language model that outputs human-like … continue reading

Snyk acquires real-time semantic code analysis provider DeepCode

Snyk is looking to bolster its security platform with the acquisition of DeepCode, a provider of real-time semantic code analysis. Through its AI-powered platform, DeepCode is able to assist developers with app quality and security. According to Snyk, the addition of DeepCode will add to its existing open-source security, container security and infrastructure as code … continue reading

end to end view of Google’s MLOps services

Google announces new services to simplify MLOps

Google has announced a new set of services aimed at simplifying Machine Learning Operations (MLOps) for data scientists and machine learning (ML) engineers. According to Google, companies are using machine learning to solve challenging problems, but machine learning systems can create unwanted technical debt if it is not managed well. Google noted that machine learning … continue reading

SD Times news digest: Instana announces direct integration of traces, LEADTOOLS version 21 released, and Half type introduced in .NET 5 Preview 7

The latest integration of traces allows Instana users to drill down into profiles related to individual requests and user traces which require investigation.   “Instana’s single-click direct path from individual traces directly to applicable process profiles makes it both easy and quick for users to get the information they need to identify CPU, Memory and Concurrency … continue reading

Use Emotional Intelligence before Artificial Intelligence

Process change is more about people than process. At least until processes can be fully automated. During the past decade, I have championed technology-led process improvement initiatives at over a dozen large companies. I have seen process improvement implemented successfully primarily when such initiatives were pursued with a healthy mix of technology and human understanding … continue reading

Analyst Watch: The rise of AI chips

Artificial intelligence (AI) is a broad field that spans academic research with ambitions to create an artificial human brain (general AI) through to practical applications of deep learning (DL), a branch of machine learning (ML, itself the part of AI concerned with learning systems built on data rather than prepared rules). DL has many real-world … continue reading

Autonomous testing: Are we there yet?

A couple of years ago, there was a lot of hype about using AI and machine learning (ML) in testing, but not a lot to show for it. Today, there are many options that deliver important benefits, not the least of which are reducing the time and costs associated with testing. However, a hands-on evaluation … continue reading

AI and ML make testing smarter… but autonomous tools are a long way from being enterprise-ready

AI and machine learning (ML) are finding their way into more applications and use cases. The software testing vendors are increasingly offering “autonomous” capabilities to help customers become yet more efficient. Those capabilities are especially important for Agile and DevOps teams that need to deliver quality at speed. However, autonomous testing capabilities are relatively new, … continue reading

A new New Relic: Focus on full-stack observability

Longtime application performance monitoring provider New Relic is shifting gears, announcing its product focus has shifted to observability with new updates to its New Relic One platform. According to the company, New Relic One has become an expanded observability platform comprised of three products: the Telemetry Data Platform, Full-Stack Observability and Applied Intelligence. The telemetry … continue reading

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