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  • Google Cloud Unveils New Tools to Unify Data

    Google Cloud Unveils New Tools to Unify Data

    Google Cloud has unveiled its latest innovations, aimed at helping companies unify database, analytics and AI.

    Google Cloud is the third leading cloud provider, behind AWS and Microsoft Azure. The company is particularly viewed as a good option for machine learning development, and has strong support for open source software.

    The company’s latest tools will go a long way toward improving its stand even further, with Dataplex, Datastream and Analytics Hub.

    Dataplex is designed to “centrally manage, monitor and govern your data across data lakes, data warehouses and data marts, and make this data securely accessible to a variety of analytics and data science tools.”

    Datastream, currently available in preview, helps “move and synchronize data between heterogeneous databases, storage and applications reliably to support real-time analytics, database replication and event-driven architectures with Datastream, our serverless change data capture (CDC) and replication service.”

    Analytics Hub is designed to make it easy to “access and share valuable datasets and analytics assets (think BigQuery ML models, Looker Blocks, data quality recipes, etc.) across any organizational boundary.” Those interested will need to sign up for preview access.

    The company’s latest tools should go a long way toward helping its customers make the most of their data, as well as AI applications.

  • Linux Foundation Tackles Data Collaboration With Permissive License

    Linux Foundation Tackles Data Collaboration With Permissive License

    The Linux Foundation has announced the CDLA-Permissive-2.0 license agreement to make it easier to share AI and ML data.

    The rise of artificial intelligence and machine learning have created a need for a new type of license that allows data sets and learning models to be shared, as well as incorporated into AI and ML applications.

    The Linux Foundation described the challenges in a blog post:

    Open data is different. Various laws and regulations treat data differently from software or other creative content. Depending on what the data is and which country’s laws you’re looking at, the data often may not be subject to copyright protection, or it might be subject to different laws specific to databases, i.e., sui generis database rights in the European Union. 

    Additionally, data may be consumed, transformed, and incorporated into Artificial Intelligence (AI) and Machine Learning (ML) models in ways that are different from how software and other creative content are used. Because of all of this, assumptions made in commonly-used licenses for software and creative content might not apply in expected ways to open data.

    While the Linux Foundation previously offered the CDLA-Permissive-1.0 license, it was often criticized for being too long and complex. In contrast, 2.0 is less than a page long and is greatly simplified over its predecessor.

    In response to perceptions of CDLA-Permissive-1.0 as overly complex, CDLA-Permissive-2.0 is short and uses plain language to express the grant of permissions and requirements. Like version 1.0, the version 2.0 agreement maintains the clear rights to use, share and modify the data, as well as to use without restriction any “Results” generated through computational analysis of the data.

    A key element of the new license is the ability to collaborate and maintain compatibility with other licenses, such as Creative Commons licenses. The addition of CDLA-Permissive-2.0 is already being met with acclaim from the industry, with both IBM and Microsoft making data sets available using the language.

    “IBM has been at the forefront of innovation in open data sets for some time and as a founding member of the Community Data License Agreement. We have created a rich collection of open data sets on our Data Asset eXchange that will now utilize the new CDLAv2, including the recent addition of CodeNet – a 14-million-sample dataset to develop machine learning models that can help in programming tasks.” Ruchir Puri, IBM Fellow, Chief Scientist, IBM Research

  • Aisera Partners With Microsoft to Deliver AI Service Desk Solutions

    Aisera Partners With Microsoft to Deliver AI Service Desk Solutions

    Aisera has become member of the Microsoft for Startups program, partnering with Microsoft to deliver AI-based service desk solutions.

    Aisera specializes next-gen AI service desks, automating requests, tickets and operations for customer service, DevOps, HR and IT. Aisera’s platform uses conversational AI and natural language processing to help deliver personalized experiences and reduce costs and resolution times.

    The companies will offer AI Service Desk on Azure, as well as AI Service Desk on Teams. 

    “Being a part of the Microsoft for Startups program is another proud moment for Aisera as we continue an era of explosive growth of the company having recently announcing a new round of funding, new customers including Dartmouth College, and exciting new integrations and partnerships that empower our enterprise-focused end-to-end automation services,” said Muddu Sudhakar, founder and CEO of Aisera. “With the support of Microsoft as a key growth partner, we are prepared to take the next step in enhancing Aisera’s services, increasing our offerings and raising our auto-resolution rates for our enterprise customers.”

    “The Microsoft for Startups program was started with the goal of assisting innovative startups, like Aisera, to escalate their growth so they can reach the enterprise businesses that need their solutions,” said Jeffrey Ma, Vice President, Microsoft for Startups. “It’s clear that Aisera will be another success story for the Microsoft for Startups program and we look forward to working alongside their team to make that happen.”

  • HPE Buys Ampool to Improve SQL-Based Hybrid Analytics

    HPE Buys Ampool to Improve SQL-Based Hybrid Analytics

    Hewlett-Packard Enterprise (HPE) has announced its acquisition of Ampool, in an effort to modernize the SQL stack.

    SQL is still one of the most widely-used database workload. With the increased adoption of cloud computing, however, SQL does have limitations. Ampool is the developer of a distributed SQL engine based on the open source Presto.

    HPE plans to use Ampool’s engine to accelerate “HPE Ezmeral analytics runtime for interactive SQL workloads.” This will help HPE better address customer needs, especially in data-intensive scenarios, such as AI, machine learning and analytics.

    “The acquisition builds on this strategy by adding Ampool’s technology components and open source expertise to the Ezmeral portfolio, which will over time turn into a set of SQL acceleration services made available through the HPE GreenLake cloud platform,” writes Anant Chintamaneni, Vice President and GM, HPTE Ezmeral. “This acquisition is also further evidence of HPE’s investment, focus and execution toward building out an open-source-based, IP rich capability for the HPE Ezmeral software portfolio, to deliver superior end to end analytics in fast growth markets.”

  • Autonomous Cars Harder to Develop Than Elon Musk Thought

    Autonomous Cars Harder to Develop Than Elon Musk Thought

    Elon Musk has admitted developing autonomous cars is harder than he thought, as the timeline for the latest software update slips again.

    Like most automakers, Tesla is working hard to crack autonomous driving, widely seen as the next big evolution for the auto industry. The company’s software has been criticized for being ‘easily tricked,’ and there have been several high-profile deaths involving Tesla’s Full Self-Driving (FSD).

    When a user poked fun on Twitter over the latest software update missing its deadline, Musk responded, acknowledging the difficulties involved.

    Musk’s admission underscores the challenges companies are facing in their effort to bring the auto industry into the future.

  • Google AI Chief Ignites Firestorm Over ‘Marginalized Groups’ Tweet

    Google AI Chief Ignites Firestorm Over ‘Marginalized Groups’ Tweet

    Google AI Chief Jeff Dean ignited a firestorm of comments on Twitter by inviting “marginalized groups” to work with Google researchers.

    Jeff Dean was at the center of the controversial firing of Dr. Timnit Gebru, a world-renowned AI ethics researcher in late 2020. At the time, Google tried to pass the situation off as Gebru resigning, but she and her team made it clear she had been fired, over an issue of academic integrity. Gebru had co-authorized a paper highlighting the dangers of certain times of AI, including the type Google regularly uses. Gebru’s co-lead, Margaret Mitchell, was fired some time later, after her outspoken support for her colleague.

    Google has already faced severe backlash for its actions. Multiple researchers and engineers have quit, independent researchers have started turning down the company’s funding, the company was removed as a sponsor for a high-profile AI conference and its remaining researchers have petitioned the company to respect academic integrity, one of the pivotal points of contention leading to Gebru’s exit.

    With such a background, it’s hard to fathom what Dean was thinking with his recent tweet, in which he said:

    I encourage students from historically marginalized groups who are interested in learning to conduct research in AI/ML, CS or related areas to consider applying for our CSRMP mentorship program! We have 100s of researchers @GoogleAI who are excited to work with you.

    Needless to say, the reaction was swift and severe, with many Twitter users asking how he could possibly expect marginalized groups to trust Google after its actions. The criticism is especially notable since the company is accused of marginalizing a Black woman, and never taking responsibility, let alone attempting to fix it.

    The backlash appears to have been swift enough to cause Dean to remove his tweet, as it is no longer available at time of writing. 

    Google’s mishandling of this situation continues to be an astounding case study of what not to do.

  • Amazon Launches Amazon Scout Development Center in Helsinki

    Amazon Launches Amazon Scout Development Center in Helsinki

    Amazon is launching a development center in Helsinki, Finland, in an effort to boost its autonomous delivery.

    Amazon Scout is the company’s autonomous delivery robot. The size of a small cooler, the robot traverses sidewalks, delivering packages in four US locations. Like many companies, Amazon is looking to expand this further and widen Scout’s usage.

    The company is launching a new development center aimed at supporting Scout and continuing its research and development. The new team will initially consist of two dozen engineers, although Amazon says the team will grow over time.

  • Zoom Acquiring Machine Translation Firm Kites

    Zoom Acquiring Machine Translation Firm Kites

    Zoom has announced it is acquiring Kites GmbH, a firm specializing in real-time Machine Translation (MT).

    As remote work and communication platforms have surged in popularity, so has the need for real-time translation. Virtually ever major platform has been working on adding translation features.

    Zoom’s latest deal should give the company’s efforts a significant boost. Kites has its roots in the academic community, and has been working to apply AI and machine learning to real-time translation.

    “We are continuously looking for new ways to deliver happiness to our users and improve meeting productivity, and MT solutions will be key in enhancing our platform for Zoom customers across the globe,” said Velchamy Sankarlingam, President of Product and Engineering at Zoom. “With our aligned missions to make collaboration frictionless – regardless of language, geographic location, or other barriers – we are confident Kites’ impressive team will fit right in with Zoom.”

    “Kites emerged with the mission of breaking down language barriers and making seamless cross-language interaction a reality of everyday life, and we have long admired Zoom for its ability to easily connect people across the world,” said Dr. Waibel and Dr. Stüker. “We know Zoom is the best partner for Kites to help advance our mission and we are excited to see what comes next under Zoom’s incredible innovation engine.”

    The Kites team will continue to be based in Karlsruhe, Germany. Terms of the deal were not disclosed.

  • Microsoft Releases OpenAI-Powered Code Completion Tool

    Microsoft Releases OpenAI-Powered Code Completion Tool

    Microsoft is leveraging its agreement with OpenAI to radically change the nature of low-code development with its first AI-powered code completion tool.

    OpenAI is an AI research organization, founded on the principle of researching AI in a safe, responsible way. OpenAI’s GPT-3 is one of the leading natural language models, and it runs exclusively on Microsoft Azure. Microsoft also has an exclusive license to the GPT-3 code, giving it wide latitude to incorporate the model in its own products.

    The partnership is bearing fruit, with Microsoft incorporating GPT-3 in its Power Apps low code development platform, adding natural, conversational language to the programming process.

    The new AI-powered features will allow an employee building an e-commerce app to describe a programming goal using conversational language like “find products where the name starts with ‘kids.’” A fine-tuned GPT-3 model then offers choices for transforming the command into a Microsoft Power Fx formula, the open source programming language of the Power Platform, such as “Filter(‘BC Orders’ Left(‘Product Name’,4)=”Kids”).

    For the time being, GPT-3’s features are limited to use with Microsoft Power Fx, but the future possibilities are visually endless.

    “Using an advanced AI model like this can help our low-code tools become even more widely available to an even bigger audience by truly becoming what we call no code,” said Charles Lamanna, corporate vice president for Microsoft’s low code application platform.

  • AI Used to Restore Rembrandt’s The Night Watch

    AI Used to Restore Rembrandt’s The Night Watch

    Artificial intelligence has crossed another milestone, being used to restore Rembrandt’s masterpiece The Night Watch.

    The Night Watch was created in 1642, but was trimmed on all four sides in 1715. Amsterdam’s Rijksmuseum has used AI to restore the missing pieces, using an early copy as the source, according to BBC News.

    “The Night Watch as it is displayed in the Rijksmuseum is etched into our collective memory. Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic,” Rijksmuseum director Taco Dibbits said.

    “It is wonderful to be able to now see with our own eyes The Night Watch as Rembrandt intended it to be seen.”

    The project is yet another example of the transformative effect AI can have on a wide range of industries.

  • NVIDIA’s LaunchPad and Fleet Command Further ‘Democratizing AI’

    NVIDIA’s LaunchPad and Fleet Command Further ‘Democratizing AI’

    NVIDIA has announced LaunchPad and Fleet Command, two programs designed to help companies deploy and manage AI applications.

    Artificial intelligence is emerging as one of the most critical technologies of the future, yet it continues to be misunderstood and mismanaged. In fact, a recent report indicated a staggering 65% of companies did not understand how the AI they were using is utilized, or how it makes the decisions they rely on it for.

    NVIDIA hopes to change that with LaunchPad and Fleet Command. Launch Pad is designed to give companies access to NVIDIA-powered software and resources to jump-start their AI development.

    “Today’s enterprises are looking for a simple, comprehensive solution that provides instant access to the resources they need to build and deploy AI with ease,” said Manuvir Das, head of Enterprise Computing at NVIDIA. “NVIDIA AI LaunchPad puts AI at the fingertips of enterprises everywhere with fully automated, hybrid-cloud infrastructure and software for every stage of the AI lifecycle.”

    Fleet Command goes even further, making it easier to securely deploy, manage and scale a company’s AI.

    “The ability to deploy and manage AI applications at the edge is one of the most complex problems facing businesses as they move toward an Internet of Things era, including smart factories, intelligent retail and smart cities,” said Das. “NVIDIA Fleet Command drives efficiency across a business, helping scale edge AI with unprecedented speed.”

    NVIDIA is already a leader in the AI field, thanks to its powerful semiconductors. With LaunchPad and Fleet Command, the company is adding to that leadership by providing what companies need to effectively utilize AI.

  • IBM Brings It’s Quantum System One to Germany

    IBM Brings It’s Quantum System One to Germany

    IBM has unveiled its first quantum computer outside the US, bringing the Quantum System One to Germany.

    Quantum computing is considered the next big evolution of computing, capable of achieving things modern computers can’t. Everything from artificial intelligence to financial markets to encryption algorithms will be impacted by quantum computing. As a result, countries around the world are racing to advance the technology.

    IBM unveiled the new computer in partnership with Fraunhofer-Gesellschaft, Europe’s largest application-oriented research organization.

    “Quantum computing opens up new possibilities for industry and society,” says  Hannah Venzl, the coordinator of Fraunhofer Competence Network Quantum Computing. “Drugs and vaccines could be developed more quickly, climate models improved, logistics and transport systems optimized, or new materials better simulated. To make it all happen, to actively shape the rapid development in quantum computing, we need to build up expertise in Europe.”

    The new computer is already hard at work, testing simulations for new materials for energy storage systems, analyzing energy supply infrastructures, financial asset portfolios and improved deep learning for machine learning applications.

    “I am very pleased about the launch of the IBM Quantum System One in Germany, the most powerful quantum computer in Europe,” said Arvind Krishna, IBM CEO (translated from German.) “This is a turning point from which the German economy, industry and society will benefit greatly. Quantum computers promise to solve completely new categories of problems that are unattainable even for today’s most powerful conventional computers.”

  • McDonald’s Testing Automated Drive-Thru Technology

    McDonald’s Testing Automated Drive-Thru Technology

    McDonald’s is testing automated drive-thru ordering technology in 10 Chicago locations.

    Restaurants are increasingly looking for ways to revolutionize their processes and streamline operations. Drive-thru operations, in particular, are ripe for change, with many companies implementing mobile ordering.

    McDonald’s is taking it a step further, testing automated voice-ordering tech, according to CNBC. So far, the pilot program is seeing 85% order accuracy, with only a fifth of orders needing to be handled by a person.

    “Now there’s a big leap from going to 10 restaurants in Chicago to 14,000 restaurants across the U.S., with an infinite number of promo permutations, menu permutations, dialect permutations, weather — and on and on and on,” said CEO Chris Kempczinski.

    If McDonald’s is able to make a go of automated ordering, it would give the company a major competitive advantage over competing fast-food chains. Relying on automated ordering tech could help the company cut down on cost. It could also serve as a template for other companies looking to do the same.

  • Rise of Skynet: AI Drones Attack Humans Without Authorization

    Rise of Skynet: AI Drones Attack Humans Without Authorization

    AI-driven drones appear to have attacked humans without authorization, according to a new report by the U.N.

    Many critics view AI technology as an existential threat to humanity, seeing some variation of the Terminator franchise’s Skynet wiping humanity out. Those critics may have just been given the strongest support yet for their fears, with AI drones attacking retreating soldiers without being instructed to.

    According to the U.N. report, via The Independent, Libyan government forces were fighting Haftar Affiliated Forces (HAF) forces.

    “Logistics convoys and retreating HAF were subsequently hunted down and remotely engaged by the unmanned combat aerial vehicles or the lethal autonomous weapons systems such as the STM Kargu-2,” read the UN report.

    What makes the Kargu so dangerous is that it’s a “loitering” drone, designed to autonomously pick its own targets based on machine learning. If one such drone isn’t dangerous enough, the Kargu has swarming abilities, enabling 20 such drones to work together in a coordinated swarm.

    “The lethal autonomous weapons systems were programmed to attack targets without requiring data connectivity between the operator and the munition: in effect, a true ‘fire, forget and find’ capability,” wrote the report’s experts.

    The incident is sure to raise questions about the ongoing safety issues surrounding AI drone use, especially in the context of military applications.

  • OpenAI Launches the OpenAI Startup Fund

    OpenAI Launches the OpenAI Startup Fund

    OpenAI, one of the leading AI companies, has established a fund to invest in AI startups, in partnership with Microsoft.

    OpenAI was co-founded by Elon Musk. Musk has long been a critic of AI, believing it represents one of the biggest existential threats humanity faces. OpenAI was founded with the goal of developing AI in a safe, responsible way.

    The OpenAI Startup Fund is a $100 million fund to help AI startups that can have a profoundly positive impact on the world. The fund was announced by OpenAI co-founder Sam Altman at Microsoft Build 2021.

    “This is not a typical corporate venture fund,” said Altman. “We plan to make big, early bets on a relatively small number of companies, probably not more than 10. And we’re looking for startups in fields where AI can have the most profound, positive impact, like healthcare, climate change and education. We’re also excited about markets where AI can drive big leaps in productivity, like personal assistants and semantic search.

    “We think that helping people be more productive with new tools is a big deal, and we can imagine brand-new interfaces that weren’t possible a year ago. These aren’t the only applications we’ll consider, but they’re at the top of our target list.”

  • 65% of Companies Can’t Explain How Their AI Works

    65% of Companies Can’t Explain How Their AI Works

    Artificial intelligence (AI) may be taking the business world by storm, but that doesn’t mean companies understand it.

    A new report by Corinium and FICO indicates that some 65% of respondent companies cannot explain how the AI they utilize makes decisions or predictions. Unfortunately, the lack of knowledge leaves companies open to AI being misused.

    “Over the past 15 months, more and more businesses have been investing in AI tools, but have not elevated the importance of AI governance and responsible AI to the boardroom level,” said Scott Zoldi, Chief Analytics Officer at FICO. “Organizations are increasingly leveraging AI to automate key processes that – in some cases – are making life-altering decisions for their customers and stakeholders. Senior leadership and boards must understand and enforce auditable, immutable AI model governance and product model monitoring to ensure that the decisions are accountable, fair, transparent, and responsible.”

    The issue is further exacerbated by a lack of agreement about what ethical standards AI must meet. While some 55% agree that AI systems should meet basic ethical standards, 43% believe they have no responsibility beyond the most basic regulatory compliance, even if the AI systems in question will impact people’s livelihoods.

    “AI will only become more pervasive within the digital economy as enterprises integrate it at the operational level across their businesses,” said Cortnie Abercrombie, Founder and CEO, AI Truth. “Key stakeholders, such as senior decision makers, board members, customers, etc. need to have a clear understanding on how AI is being used within their business, the potential risks involved and the systems put in place to help govern and monitor it. AI developers can play a major role in helping educate key stakeholders by inviting them to the vetting process of AI models.”

    The report shows how far industries have to go before AI can be trusted to handle the kinds of decisions many tech leaders are eager to thrust upon it.

  • Microsoft Integrates GPT-3 Into Power Apps Low Code Development

    Microsoft Integrates GPT-3 Into Power Apps Low Code Development

    Microsoft is integrating GPT-3 — a natural language model developed by OpenAI — with its low-code development tools.

    Microsoft Power Apps is the company’s low-code development platform, designed to allow individuals to create software with minimal coding experiencing. GTP-3 is a natural language model developed by OpenAI, the artificial intelligence company that was co-founded by Elon Musk.

    By combining GTP-3 and Power Apps, Microsoft hopes to revolutionize low-code development, alowing individuals to program using natural expression commands.

    Microsoft’s Jennifer Langston outlined the benefits in a company blog post:

    For instance, the new AI-powered features will allow an employee building an e-commerce app to describe a programming goal using conversational language like “find products where the name starts with ‘kids.’” A fine-tuned GPT-3 model then offers choices for transforming the command into a Microsoft Power Fx formula, the open source programming language of the Power Platform, such as “Filter(‘BC Orders’ Left(‘Product Name’,4)=”Kids”).

    Integrating GPT-3 into Power Apps will help the company’s development tools go from low-code to no-code.

    “Using an advanced AI model like this can help our low-code tools become even more widely available to an even bigger audience by truly becoming what we call no code,” said Charles Lamanna, corporate vice president for Microsoft’s low code application platform.

    “This will allow people to query and explore data in ways they literally couldn’t do before, and that will be the magical moment,” Lamanna added.

  • Germany Clearing Autonomous Vehicles for Regular Use

    Germany Clearing Autonomous Vehicles for Regular Use

    Germany is poised to be the first country to clear autonomous vehicles for everyday use.

    According to Deutsche Welle, Germany’s lower house of parliament has passed a bill that paves the way for autonomous vehicle integration, with the bill moving to the upper chamber for passage. The bill would allow autonomous vehicles to be a standard part of daily traffic, with minimal restrictions.

    “Individual permits, exceptions and requirements — such as the presence of a safety assurance driver who is always ready to intervene — would not be necessary,” the Transportation Ministry said in a statement.

    In order to qualify, however, they must be Level 4 autonomous vehicles. Autonomous vehicles are ranked (via TechRepublic) from Level 0 to Level 5, with Level 0 having no autonomous ability and Level 5 requiring no human control whatsoever. Level 4 is still considered “fully autonomous,” even though it may not cover every conceivable driving scenario. Instead, Level 4 is focused on “operational design domain (ODD)” performance.

    Currently, there are no Level 4 vehicles available. In fact, Honda recently made headlines when it announced the world’s first Level 3 autonomous vehicle. As a result, it may be some time before there are vehicles available that meet Germany’s threshold. Nonetheless, once the bill goes into effect, Level 4 vehicles should be approved as of 2022.

    “Germany will be the first country worldwide to take autonomous vehicles from the research laboratories to the streets,” said Transportation Minister Andreas Scheuer in a statement. “We are now a major step closer to that goal.

  • California DMV Reviewing Tesla Over Self-Driving Claims

    California DMV Reviewing Tesla Over Self-Driving Claims

    Tesla is currently “under review” by California’s DMV to determine if the company’s Full Self-Driving (FSD) technology claims were misleading.

    Like many companies, Tesla has been working toward autonomous driving technology. Autonomous driving software is ranked on a scale of 0 to 5, with 0 having no autonomous capabilities and 5 requiring no driver control. Currently, Tesla’s FSD is considered a Level 2 technology. Tesla’s tech has recently come under fire for being easily fooled and endangering people’s lives.

    In spite of its limitations, Musk has touted FSD, even going so far as to exaggerate claims about the technology. Those exaggerations have helped bring unwanted scrutiny on Tesla, with The L.A. Timesreporting the California DMV is reviewing the company’s claims. In particular, the company’s labeling its technology as “self-driving,” let alone “Full Self-Driving,” could pose legal issues.

    “Tesla seems to be asking for legal trouble on many fronts,” law professor Bryant Walker Smith told the L.A. Times. “From the FTC and its state counterparts for deceptive marketing. From the California DMV for, potentially, crossing into the realm of autonomous vehicle testing without state approval, from competitors with driver assistance systems, competitors with actual automated driving systems, ordinary consumers, and future crash victims who could sue under state or federal law.”

    Although California law holds the driver responsible for any accidents, the DMV still has the authority to impose penalties on companies that make misleading claims. The penalties could range from withholding autonomous deployment permits to revoking manufacturing and dealership licenses.

  • Skyborg AI Flies Air Force Drone — What Could Possibly Go Wrong?

    Skyborg AI Flies Air Force Drone — What Could Possibly Go Wrong?

    Combine Skynet from Terminator and the Borg from Star Trek and you have Skyborg, also known as the latest Air Force AI that has successfully flown a drone.

    As any avid science fiction fan can attest, there are some things that are just not a good idea. Creating an AI designed to autonomously fly fighter drones seems like one of them, but naming it after a combination of two of the most terrifying technological villains in moviedom takes the cake.

    The Air Force developed two flavors of Skyborg. The first flavor — which we covered here — is an R2-D2 inspired copilot AI. The second is a fully autonomous system that can fly a pilotless drone.

    The Air Force’s goal is to eventually have the Skyborg Autonomy Core System (ACS) fly dangerous missions that currently require putting a pilot in harm’s way. The latest test, over Florida and the Gulf of Mexico, was a big step in that direction.

    “We’re extremely excited for the successful flight of an early version of the ’brain‘ of the Skyborg system,” said Brig. Gen. Dale White. “It is the first step in a marathon of progressive growth for Skyborg technology,” White said. “These initial flights kick off the experimentation campaign that will continue to mature the ACS and build trust in the system.”

    “This test is a significant step toward teaming manned and unmanned aircraft in combat in the not-too-distant future,” said Maj. Nathan McCaskey, 40th Flight Test Squadron Test Pilot and AAAx Project Pilot. “Unmanned aircraft using the autonomy system developed for this experiment could go places where manned fighters can’t go, providing sensor information back to manned teammates, increasing the power projection capability of the Air Force.”

    The Air Force hopes to have fully operational Skyborg craft flying missions around 2023. If science fiction is any guide, humanity should be fighting for its life shortly thereafter.

  • IBM Introduces Project CodeNet to Aid AI Code Translation

    IBM Introduces Project CodeNet to Aid AI Code Translation

    IBM is using its 2021 Think Conference to tout its advances in artificial intelligence (AI), including Project CodeNet.

    One of the biggest challenges many companies face is translating existing codebases into another language. Artificial intelligence (AI) promises to help alleviate that problem, but requires extensive training to properly translate from one programming language to another.

    IBM Research has released Project CodeNet, a dataset aimed at training AIs in source-to-source translation.

    A large dataset aimed at teaching AI to code, it consists of some 14M code samples and about 500M lines of code in more than 55 different programming languages, from modern ones like C++, Java, Python, and Go to legacy languages like COBOL, Pascal, and FORTRAN.

    IBM says Project CodeNet is “the largest, most differentiated dataset in its class and addresses three main use cases in coding today: code search (automatically translating one code into another, including legacy languages like COBOL); code similarity (identifying overlaps and similarities among different codes); and code constraints (customizing constraints based on a developer’s specific needs and parameters).”

    The company believes Project CodeNet will help revolutionize source-to-source language translation, and could be a vital resource for companies that need to move legacy codebases to modern languages.