Displaying items by tag: Machine Learning
Microsoft and Altran, the design and engineering firm recently acquired by Capgemini, have collaborated to develop an AI-based tool to predict the likelihood of bugs in source codes created by developers early in the software development process.
By applying machine learning (ML) to historical data, the tool – called “Code Defect AI” – identifies areas of the code that are potentially buggy and then suggests a set of tests to diagnose and fix the flaws, resulting in higher-quality software and faster development times.
Bugs are a fact of life in software development. The later a defect is found in the development lifecycle, the higher the cost of fixing a bug. This bug-deployment-analysis-fix process is time consuming and costly. Code Defect AI allows earlier discovery of defects, minimizing the cost of fixing them and speeding the development cycle.
“It’s well known that software developers are under constant pressure to release code fast without compromising on quality,” said Walid Negm, Group Chief Innovation Officer at Altran.
“The reality however is that the software release cycle needs more than automation of assembly and delivery activities. It needs algorithms that can help make strategic judgments ‒ especially as code gets more complex. Code Defect AI does exactly that.”
Code Defect AI relies on various ML techniques including random decision forests, support vector machines, multilayer perceptron (MLP) and logistic regression. Historical data is extracted, pre-processed and labelled to train the algorithm and curate a reliable decision model. Developers are given a confidence score that predicts whether the code is compliant or presents the risk of containing bugs.
Code Defect AI supports integration with third-party analysis tools and can itself help identify bugs in a given program code. Additionally, the Code Defect AI tool allows developers to assess which features in the code have higher weightage in terms of bug prediction, i.e., if there are two features in the software that play a role in the assessment of a probable bug, which feature will take precedence.
“Microsoft and Altran have been working together to improve the software development cycle, and Code Defect AI, powered by Microsoft Azure, is an innovative tool that can help software developers through the use of machine learning,” said David Carmona, General Manager of AI Marketing at Microsoft.
Code Defect AI is a scalable solution that can be hosted on premise as well as on cloud computing platforms such as Microsoft Azure. While the solution currently supports GitHub, which is owned by Microsoft, it can be integrated with other source-code management tools as needed.
The World Economic Forum launched six Industry 4.0 Councils on Wednesday to aid policymakers and enterprises in leveraging emerging technologies whilst anticipating the social risks that could result from them.
Nokia and Inria, a French national research institute dedicated to promoting 'scientific excellence in the service of technology transfer and society as a whole', announced the renewal of their joint lab for a four-year period. The announcement took place during an event celebrating the 50th anniversary of Inria with Marcus Weldon, Nokia CTO and Nokia Bell Labs President, and Antoine Petit, Inria CEO.
"Nokia Bell Labs collaborates with the best academic teams in the world on solving the key technical challenges confronting humankind. Together, Inria and Bell Labs are collaborators and co-pioneers in this endeavor, with a rich and fruitful relationship over the past 20 years,” said Marcus Weldon, Nokia Chief Technical Officer and Nokia Bell Labs President.
“We have even higher expectations and plans for our future collaboration via our common laboratory centered on addressing the fundamental challenges of humans in the future connected world,” Weldon added.
Launched in 2008, the joint lab associates permanent researchers from the two partners with PhD students and postdoctoral researchers, sharing the same strategic vision to solve the key scientific challenges linked to the evolution of networks and network applications. The aim of this joint research is to offer users the benefits from required network and cloud resources for a contextual and personalized experience of the digital connected world.
The future networks will have to manage a multitude of connected objects, to host and interconnect massively distributed functions, to feature an unprecedented agility to support differentiated and demanding use cases like the connected car, industry 4.0, smart city and e-health. This will require strong guarantees in terms of security and privacy, while hiding the complexity through a high level of automation.
To achieve this aim, this new phase of the common lab will associate advanced research in information theory, machine learning, graph theory, game theory, cybersecurity, network virtualization and advanced control software.
The scope of the collaboration covers several research actions dedicated to information theory and algorithms to solve the challenges of IoT; analytics and machine learning to dynamically and automatically optimize the virtualized network; scalable distributed learning and control for augmented intelligence to operate complex IoT networks of dynamic elements; and cybersecurity to provide privacy, data integrity and resilience against intrusions.
"Inria develops the whole scope from research to applications in the area of computer science and applied mathematics. With leading companies, we operate joint labs that are focused on long term cooperation,” said Antoine Petit, Inria CEO.
“With Nokia Bell Labs we develop technologies that will power the future of networks and telecommunication. Our common goal is to produce new scientific results as well as new innovations that can enrich the technologies and products developed by Nokia. It is the DNA of Inria to go from high level research to industrial applications."
Chinese AI firm SenseTime and Qualcomm Technologies announced plans to collaborate on artificial intelligence (AI) and machine learning (ML) for future mobile and IoT products. This collaboration will draw from the expertise of both companies in AI by leveraging SenseTime’s ML models and algorithms with Qualcomm Snapdragon platforms, which offer advanced computing capabilities for client based AI.
“To develop an AI ecosystem, it takes efforts from players in multiple industries,” said Dr Li Xu, co-founder and CEO of SenseTime. “The strategic collaboration between SenseTime and Qualcomm Technologies will advance on-device intelligence by leveraging our algorithm and Qualcomm Technologies’ chipset. Together we’ll push the envelope and extend AI to places that are currently beyond reach.”
Devices such as smartphones and connected cameras are becoming more intelligent with the proliferation of AI. The companies expect to drive the popularity and development of on-device AI in areas such as innovative vision and camera-based image processing.
Implementing AI on the device provides a number of advantages over cloud-only implementations, enabling edge devices to provide reliable execution with or without a network connection. Additional benefits of on-device AI include real-time performance, privacy protection and enhanced reliability.
“Qualcomm has been conducting fundamental research in AI over a decade,” said Keith Kressin, senior vice president, product management, Qualcomm Technologies. “In fact, many devices shipping today using our Snapdragon mobile platforms already utilize on-device AI. We look forward to the results of our collaboration with SenseTime to further accelerate new and exciting capabilities of on-device AI for millions of customers using mobile devices.”
Currently, Qualcomm Technologies is focused on optimizing the Snapdragon mobile platform to accelerate myriad AI use cases in the areas of computer vision and natural language processing — for smartphones, IoT and automotive — and is researching broader executions in the areas of wireless connectivity, power management, and photography.
SenseTime is a leading company in artificial intelligence and its applications. It plays an important role in deep learning algorithm innovation and has built a proprietary deep learning platform called Parrots. The company's deep learning technology makes it possible to innovate and develop a variety of algorithms with low cost and quick turn-around.
SenseTime has made breakthroughs in algorithm model miniaturization. Its strategic collaboration with Qualcomm Technologies is expected to drastically improve the speed and efficiency of combining algorithm and chipset, making SenseTime's AI technology more pervasive.
The United States is planning to increase its scrutiny of Chinese investment in Silicon Valley in an effort to protect what it describes as ‘sensitive technologies’ which are seen as vital to US national security. China has shown a particular interest in AI and machine learning and both technologies have received a significant amount of Chinese capital in recent years.
The US has expressed concern that the cutting-edge technologies being developed in the US could be used by China to bolster its own military capabilities. However, the US government has now taken steps to strengthen the role of the Committee on Foreign Investment in the US, which is the inter-agency committee that reviews foreign acquisitions of US companies on security grounds.
It has been disclosed that an unpublished Pentagon report has raised concerns that China is skirting with US oversight in relation to gaining access to sensitive technology through transactions that don’t currently trigger CFIUS review. A member of the Trump administration said they had the review CFIUS due to the ‘predatory practices’ of China. The official who was not granted authority to speak said, “We're examining CFIUS to look at the long-term health and security of the U.S. economy, given China's predatory practices in technology.”
Under the administration of former US president Barack Obama – CFIUS prevented a number of attempted Chinese acquisitions of high-end chip makers. One Republican in the senate, John Cornyn, is currently drafting legislation which would enable the CFIUS to have much more power to block technology investments it expresses concern about.
A spokesman for the Senator said, “Artificial intelligence is one of many leading-edge technologies that China seeks, and that has potential military applications. These technologies are so new that our export control system has not yet figured out how to cover them, which is part of the reason they are slipping through the gaps in the existing safeguards.”
It is believed one of the most contentious issues over Chinese investment in advanced technology comes at a time when the US military looks to incorporate elements of AI and machine learning into its drone program. The program which has been entitled ‘Project Maven’ has been specifically designed to provide relief to military analysts who are part of the war against Islamic State. Analysts currently have to endure spending long hours staring at big screens reviewing video feeds from drones as part of its attempts to snuff out the threat of insurgents in war-torn places such as Iraq and Afghanistan.
China has made no attempts to hide its ambition to become a major player in developing technologies such as AI, through a series of foreign acquisitions. In March, China search engine colossus Baidu Inc. launched an AI in conjunction with China’s state planner the National Development and Reform Commission. On example of this was Baidu’s decision in April to acquire U.S. computer vision firm xPerception, which makes vision perception software and hardware with applications in robotics and virtual reality. “China is investing massively in this space," said Peter Singer, an expert on robotic warfare at the New America Foundation.