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Xilinx launches Kria chips to handle AI for edge applications

#artificialintelligence

Xilinx has introduced its Kria programmable chips and boards for holding AI applications at the edge of the network. This should come in handy for visual applications like smarter cameras. San Jose, California-based Xilinx, which is in the process of being acquired by Advanced Micro Devices (AMD) for $35 billion, has a group of products dubbed the Kria portfolio of adaptive system-on-module offerings for AI at the edge. These are production-ready small form factor embedded boards that enable rapid deployment in edge-based applications. Coupled with a complete software stack and prebuilt, production-grade accelerated applications, Kria adaptive modules are a new method of bringing adaptive computing to AI and software developers.


Researchers open-source benchmarks measuring quality of AI-generated code

#artificialintelligence

The applications of computer programming are vast in scope. And as computers become ubiquitous, the demand for quality code draws an ever-growing number of aspiring programmers to the profession. After years of study to become proficient at coding, experts learn to convert abstracts into concrete, executable programs. But what if AI could do the same? In recent years, large-scale AI language models have shown promise in generalizing to tasks including writing code, implying that humans' work may be one day supplemented by AI systems.


Microsoft announces first product features running on GPT-3

#artificialintelligence

During its Build developers conference this year, Microsoft announced its first features for a product fueled by GPT-3, the natural language model from OpenAI developed to assist users in building applications without any programming knowledge. GPT-3 will come into play through Microsoft Power Apps, the low code app development platform that a helps a wide range of folks from those with no programming experienced to those considered experienced developers. So far, this platform has aided in the development of apps for travel during COVID-19, review of nonprofit gift donation and decreasing the amount of overtime needed for wind turbine maintenance. For example, the AI-powered platform will allow users to search for e-commerce products with a query such as "Find products where the name starts with'kids,'" similar to SQL. An efficient GPT-3 model will then convert that query as a formula into the open source Power Platform language, Microsoft Power Fx. Microsoft claims that this new platform solution will greatly benefit enterprises by using its new managed endpoints capability to solve real-world business problems, backed by familiar components such as Microsoft Azure for operation and Azure Machine Learning as a power source.


Microsoft to make coding 'in plain English' easier with PowerFx and GPT-3 AI model

#artificialintelligence

Microsoft is integrating AI technologies with its PowerFx low-code programming language. This integration will enable customers to use natural-language input and "programming by example" techniques when developing with PowerApps. Microsoft announced the coming new capabilities during the opening day, May 25, of its virtual Build 2021 developers conference. Officials said these new features will be in public preview in English throughout North America by the end of June. PowerFx is the low-code textual programming language Microsoft announced earlier this year.


AI Could Soon Write Code Based on Ordinary Language

WIRED

In recent years, researchers have used artificial intelligence to improve translation between programming languages or automatically fix problems. The AI system DrRepair, for example, has been shown to solve most issues that spawn error messages. But some researchers dream of the day when AI can write programs based on simple descriptions from non-experts. On Tuesday, Microsoft and OpenAI shared plans to bring GPT-3, one of the world's most advanced models for generating text, to programming based on natural language descriptions. This is the first commercial application of GPT-3 undertaken since Microsoft invested $1 billion in OpenAI last year and gained exclusive licensing rights to GPT-3.


Microsoft deploys GPT-3 to let devs code using everyday language

#artificialintelligence

Microsoft has announced its first commercial use case for AI language model GPT-3, for which the company purchased an exclusive license last year. Developed by OpenAI, GPT-3 is capable of generating accurate passages of text based on only a few basic prompts. Soon after the model was released, one tester also found it could be taught to compose code with just a few tweaks, leading to speculation over how Microsoft might utilize the technology. At its Build 2021 event, Microsoft has revealed that GPT-3 will be put to work in combination with Power Fx, the company's low-code open source programming language. The pairing will allow developers to code applications using natural language inputs, expediting application development and helping devs pick up advanced concepts more quickly.


Microsoft has built an AI-powered autocomplete for code using GPT-3

#artificialintelligence

In September 2020, Microsoft purchased an exclusive license to the underlying technology behind GPT-3, an AI language tool built by OpenAI. Now, the Redmond, Washington-based tech giant has announced its first commercial use case for the program: an assistive feature in the company's PowerApps software that turns natural language into readymade code. The feature is limited in its scope and can only produce formulas in Microsoft Power Fx, a simple programming language derived from Microsoft Excel formulas that's used mainly for database queries. But it shows the huge potential for machine learning to help novice programmers by functioning as an autocomplete tool for code. There's a million-developer shortfall in the US alone," Charles Lamanna, CVP of Microsoft's Low Code Application Platform, tells The Verge. "So instead of making the world learn how to code, why don't we make development environments speak the language of a normal human?" Microsoft has been pursuing this vision for a while through Power Platform, its suite of "low code, no code" software aimed at enterprise customers. These programs run as web apps and help companies that can't hire experienced programmers tackle basic digital tasks like analytics, data visualization, and workflow automation. GPT-3's talents have found a home in PowerApps, a program in the suite used to create simple web and mobile apps. Lamanna demonstrates the software by opening up an example app built by Coca-Cola to keep track of its supplies of cola concentrate. Elements in the app like buttons can be dragged and dropped around the app as if the users were arranging a PowerPoint presentation. But creating the menus that let users run specific database queries (like, say, searching for all supplies that were delivered to a specific location at a specific time) requires basic coding in the form of Microsoft Power Fx formulas. "This is when it goes from no code to low code," says Lamanna. "You go from drag and drop, click click click, to writing formulas.


Microsoft to make coding 'in plain English' easier with PowerFx and GPT-3 AI model

ZDNet

Microsoft is integrating AI technologies with its PowerFx low-code programming language. This integration will enable customers to use natural-language input and "programming by example" techniques when developing with PowerApps. Microsoft announced the coming new capabilities during the opening day, May 25, of its virtual Build 2021 developers conference. Officials said these new features will be in public preview in English throughout North America by the end of June. PowerFx is the low-code textual programming language Microsoft announced earlier this year.


CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing

arXiv.org Artificial Intelligence

Currently, a growing number of mature natural language processing applications make people's life more convenient. Such applications are built by source code - the language in software engineering. However, the applications for understanding source code language to ease the software engineering process are under-researched. Simultaneously, the transformer model, especially its combination with transfer learning, has been proven to be a powerful technique for natural language processing tasks. These breakthroughs point out a promising direction for process source code and crack software engineering tasks. This paper describes CodeTrans - an encoder-decoder transformer model for tasks in the software engineering domain, that explores the effectiveness of encoder-decoder transformer models for six software engineering tasks, including thirteen sub-tasks. Moreover, we have investigated the effect of different training strategies, including single-task learning, transfer learning, multi-task learning, and multi-task learning with fine-tuning. CodeTrans outperforms the state-of-the-art models on all the tasks. To expedite future works in the software engineering domain, we have published our pre-trained models of CodeTrans. https://github.com/agemagician/CodeTrans


Towards A Process Model for Co-Creating AI Experiences

arXiv.org Artificial Intelligence

Thinking of technology as a design material is appealing. It encourages designers to explore the material's properties to understand its capabilities and limitations, a prerequisite to generative design thinking. However, as a material, AI resists this approach because its properties emerge as part of the design process itself. Therefore, designers and AI engineers must collaborate in new ways to create both the material and its application experience. We investigate the co-creation process through a design study with 10 pairs of designers and engineers. We find that design 'probes' with user data are a useful tool in defining AI materials. Through data probes, designers construct designerly representations of the envisioned AI experience (AIX) to identify desirable AI characteristics. Data probes facilitate divergent thinking, material testing, and design validation. Based on our findings, we propose a process model for co-creating AIX and offer design considerations for incorporating data probes in design tools.