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AI ethics: How Salesforce is helping developers build products with ethical use and privacy in mind

ZDNet

People have long debated what constitutes the ethical use of technology. But with the rise of artificial intelligence, the discussion has intensified as it's now algorithms not humans that are making decisions about how technology is applied. In June 2020, I had a chance to speak with Paula Goldman, Chief Ethical and Humane Use Officer for Salesforce about how companies can develop technology, specifically AI, with ethical use and privacy in mind. I spoke with Goldman during Salesforce's TrailheaDX 2020 virtual developer conference, but we didn't have a chance to air the interview then. I'm glad to bring it to you now, as the discussion about ethics and technology has only intensified as companies and governments around the world use new technologies to address the COVID-19 pandemic. The following is a transcript of the interview, edited for readability. Bill Detwiler: So let's get right to it.


A love letter to the brain: in his new book on AI, Jeff Hawkins is enamored of thought

ZDNet

"There are a lot of people talking about AI as this huge existential threat, but I don't see it that way," says Hawkins. "Gosh, look at what computing has done done for us; I think AI will be even bigger." We live inside a body ruled by a brute, and the question of humanity my be whether we ever rise up and defy that brute. Such is, in rough outline, the key question of the human race's future in A Thousand Brains, the new book about artificial intelligence, and also, surprisingly, about human impulses, by Jeff Hawkins, which went on sale this week. "What's the purpose of living, why are we here, what would be a good goal for humanity," Hawkins mused during a conversation about the book with ZDNet via Zoom last week. "Intelligence is the thing that defines us, the thing we want to preserve and propagate."


A hip-fired electromagnetic anti-drone rifle

ZDNet

A new anti-drone kit billed as the Swiss Army Knife of drone defenses just debuted from French company CERBAIR. The drone detection and mitigation tool--the business end of which is a hip-fired electromagnetic rifle--is emblematic of a growing urgency to develop security tools for guarding against rogue drone attacks. The prevalence and growing sophistication of drones has created a serious obstacle for law enforcement. Commercially available drones can be used to threaten government officials and carry out attacks during public gatherings and events. A joint multi-agency threat assessment issued prior to then-incoming President Biden's inauguration listed drones as a potential threat.


Apps, drone deliveries and AI: How technology stepped up its game to fight COVID-19

ZDNet

For the past few months, an independent board of technology experts has been closely tracking the new ways that AI and data have been used to counter and mitigate the effects of the COVID-19 pandemic in the UK; and now, they are lifting the veil on the good, the bad and the ugly of the past year in digital tech. The Center for Data Ethics and Innovation (CDEI) has released a new report diving deep into the 118 individual use-cases for AI and data-driven technologies that have been added to the organization's COVID-19 repository since last November. Spanning vastly different sectors and locations, the examples collated in the document provide a unique vision of the ways that technology can help in a time of crisis. From piloting drones to delivering medical supplies, to monitoring the behavior of residents in public transport during the easing of lockdown restrictions: if there is one observation that all experts will agree on, it is certainly that technology has been a central pillar in the support of the response to the pandemic. "While public attention largely centred on high-profile applications aimed at either suppressing the virus or coping with its effects, our research highlights the breadth of applications beyond these two use-cases," says the report.


Boundless: The evolution of the connected company

ZDNet

"The world of reality has its limits; the world of imagination is boundless." Over the last two years or so, Henry King, innovation and transformation at Salesforce and my colleague and co-author, and I have been investigating and reporting on a model for business success that has eluded the spotlight until now but is beginning to emerge into the mainstream. It contrasts traditional or conventional ways of managing a company's various resources (data, product, money, employees, customers, etc.) with new ones that we have seen gradually emerging over at least a decade. The primary driver of change during this period has been and continues to be, the evolution of our digital technologies and the new opportunities they bring to those able to perceive and assimilate them, as well of course as the new challenges they bring to those who aren't. The gulf between opportunity and challenge, between success and failure, was made manifest by the COVID-19 pandemic which quickly became the accelerant of digital adoption at least for the connection between businesses and their customers and employees in a digital-first, work from anywhere -- in fact do anything from anywhere -- world.


AI: Facebook's new algorithm was trained on one billion Instagram pics

ZDNet

Facebook's researchers have unveiled a new AI model that can learn from any random group of unlabeled images on the internet. Facebook's researchers have unveiled a new AI model that can learn from any random group of unlabeled images on the internet, in a breakthrough that, although still in its early stages, the team expects to generate a "revolution" in computer vision. Dubbed SEER (SElf-SupERvised), the model was fed one billion publicly available Instagram images, which had not previously been manually curated. But even without the labels and annotations that typically go into algorithm training, SEER was able to autonomously work its way through the dataset, learning as it was going, and eventually achieving top levels of accuracy on tasks such as object detection. The method, aptly named self-supervised learning, is already well-established in the field of AI: it consists of creating systems that can learn directly from the information they are given, without having to rely on carefully labeled datasets to teach them how to perform a task such as recognizing an object in a photo or translating a block of text.


Accenture acquires Brazilian robotics and automation firm Pollux

ZDNet

Consulting firm Accenture announced it has agreed to acquire Pollux, a Brazil-based company providing industrial robotics and automation systems as part of its strategy to boost its digital manufacturing, operations and supply chain capabilities. The terms of the acquisition have not been disclosed. The deal follows Accenture's acquisition of information security firm Real Protect in Januay 2021 and cloud specialist Organize Cloud Labs in August 2020. Pollux designs, engineers and deploys fully functional assembly lines that include robots and other hardware, plus the software that controls them. It also develops visual analytics inspection solutions, autonomous mobile robots and robots as a service for shop floors and warehouses to optimize manufacturing and logistics processes.


Xero expands small business offering with Planday acquisition

ZDNet

Xero has announced it will buy out Denmark-based workforce management platform Planday in a move to further grow its position in the small business market. Planday is cloud-based platform that's been designed to provide businesses with a real-time view of staffing needs and payroll costs, alongside business performance metrics. "The acquisition of Planday aligns with our purpose to make life better for people in small businesses and their advisors," Xero CEO Steve Vamos said. "Planday's workforce management platform helps small businesses to respond to the rapidly changing nature of work. Planday also addresses the growing need for flexibility and rising compliance demands within the workplace."


Streamlining data science with open source: Data version control and continuous machine learning

ZDNet

MLOps, short for machine learning operations, is the equivalent of DevOps for machine learning models: Taking them from development to production, and managing their lifecycle in terms of improvements, fixes, redeployments, and so on. Achieving MLOps nirvana is a major barrier to getting value out of machine learning and data science. Version control systems like Git and practices like continuous integration / continuous deployment (CI/CD) have helped operationalize software development. What if those systems and practices could also be used for MLOps? Data engineers, machine learning, and data science practitioners work with a wide range of data.


Quantum sensors could soon be heading into space

ZDNet

An outer-space mission inevitably calls for next-generation tools. Quantum technologies are on track to reach new heights – quite literally: quantum company Q-CTRL has plans to send ultra-sensitive quantum sensors and navigation devices to space, as part of a mission to explore the moon for water and other resources that will support NASA astronauts in future landings. The Australian company, which applies the principles of control engineering to improve the hardware performance of quantum devices, will provide the quantum technology to assist un-crewed missions organized by the Seven Sisters space industry consortium, and planned to start in 2023. Formed last year by space start-up Fleet Space, the consortium is working to send nanosatellites and exploration sensors to the moon to search for resources, and generate useful data for future human exploration. The information gathered will inform NASA's Artemis program, which will land the first woman and next man on the Moon by 2024, creating a sustainable human presence for later crewed Martian exploration.