Artificial Intelligence and Machine Learning explained

AI, or artificial intelligence, is technology that attempts to simulate human cognitive function. A  popular use case right now is ChatGPT, which allows you to conversationally ask questions to a chatbot and get back relevant information because the AI can understand what you’re asking in plain language. Beyond just answering questions, these AIs are capable of writing code, creating detailed plans based on your specifications, summarizing documents, and more.

AI has made its way into the software development space in a number of ways. AI can be baked into applications to improve end user experience by creating personalized recommendations and tailoring experiences to the end user. AI-assisted development tools can complete the piece of code you started writing, or even offer suggestions for how to improve your code. Generative AI chatbots, such as ChatGPT, can be used to ask for specific code snippets to perform a task, can explain what is happening in a piece of code, or can be used to troubleshoot why your code isn’t working as intended.

Read the articles below for more information on what you need to know about AI.

Microsoft Copilot will embed AI assistance across entire Windows 11 ecosystem

Microsoft is announcing Microsoft Copilot, a general AI copilot that will work across the entire Windows platform. Previously the company has released other AI copilots, such as the new AI-powered search in Bing, and Microsoft 365 Copilot, which works across Microsoft 365 apps like Word, Excel, PowerPoint, Outlook, and Teams. “Today we take the next … continue reading

Take advantage of AI-augmented software testing

The artificial intelligence-augmented software-testing market continues to rapidly evolve. As applications become increasingly complex, AI-augmented testing plays a critical role in helping teams deliver high-quality applications at speed.  By 2027, 80% of enterprises will have integrated AI-augmented testing tools into their software engineering toolchain, which is a significant increase from 10% in 2022, according to … continue reading

Amazon announces new developer tools for building with Alexa

Amazon has unveiled the future of Alexa, revealing plans to harness the power of a specialized large language model (LLM) optimized for voice interactions. This development is expected to enhance the user experience with Alexa, making interactions more natural and conversational. The company emphasized the importance of involving developers in this journey to shape and … continue reading

Bard now connects to Google apps and services

Google has unveiled its most advanced model of its conversational AI, Bard, to date, introducing enhanced integration with Google apps and services to provide more helpful responses. Additionally, Bard has refined its “Google it” feature to verify answers, and its expanded capabilities are now available in a wider range of contexts and Google applications, including … continue reading

New Amazon Bedrock preview feature allows foundation models to connect to company data sources

AWS has announced a new feature that will let companies connect their own data sources to foundation models (FMs), which are general AI models that are trained on a large set of data and then can be adapted further for specific uses.   This is an extension of the company’s recent announcement for Amazon Bedrock that … continue reading

Perforce adds generative AI to test automation platform

Perforce Software, a DevOps solutions provider, has introduced Test Data Pro by BlazeMeter, an advanced component of its continuous testing platform.  Test Data Pro utilizes AI technology to streamline and make test data generation more accessible. The primary goal is to address the significant challenge of obtaining accurate and synchronized test data, which is particularly … continue reading

Advanced AI assistant Planview Copilot launched

Project management company Planview has unveiled Planview Copilot, an advanced AI assistant designed for connected work, during its annual event, Planview Accelerate.  This AI assistant, trained using a comprehensive dataset, provides operational insights in Portfolio Management, Value Stream Management, and Agile Planning and Delivery. It aims to expedite data-driven strategic decision-making through a conversational interface. … continue reading

Teradata enables any user to do data analysis with latest generative AI-powered capability

Teradata has introduced a generative AI feature called for VantageCloud Lake. This feature enables authorized users to ask questions about their company’s data and get immediate responses from VantageCloud Lake, a comprehensive cloud analytics and data platform for AI. The introduction of reduces the need for complex coding and querying, resulting in significant … continue reading

Report: Only 23% of development teams have implemented AI already

Only 23% of development teams are actually implementing AI today in their software development life cycle.  This is according to GitLab’s State of AI in Software Development report, which surveyed over 1,000 DevSecOps professionals in June 2023.   Despite low adoption now, when you add in the number of teams planning to use AI, that number … continue reading

SD Times Open-Source Project of the Week: Contrast Security Generative AI Policy

The main goal of this project created by Contrast Security is to create a clear and usable policy for managing privacy and security risks when utilizing Generative AI and Large Language Models (LLMs) in organizations, according to the project’s GitHub page.  The policy primarily aims to address several key concerns: 1. Avoid situations where ownership … continue reading

Slack AI, Slack Lists, and new automation capabilities released

Salesforce has introduced new features in Slack that incorporate advanced AI, automation, and knowledge-sharing capabilities into its productivity platform.  Slack AI is built natively into Slack on its trusted foundation, grounded in a company’s collective knowledge found in Slack, and easy to access in the flow of work. Using AI, channel recaps in Slack provide … continue reading

Training the models for testing

Code coverage and end-to-end testing – sometimes called path testing – are particularly well-suited for automation, but they’re only as good as the training and implementation. Since AI doesn’t have an imagination, it is up to the model and whoever is feeding in that data to cover as many paths as you can in an … continue reading

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