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Forget user experience. AI must focus on 'citizen experience'

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Tech giants and their AI-powered digital platforms and solutions can affect the destinies of world leaders, nation states, multinational corporations, global stock market, and individuals alike. The creators of major digital platforms as well as the designers and developers of ubiquitous AI systems treat individuals as mere users, customers, or data points, oftentimes completely ignoring the individual's role and rights as a citizen. As a result, the individual users and customers are removed from the societal context with appalling consequences. The individual can unconsciously become a misinformation-spreading user. A misinformed customer can turn into a violent insurgent.


How Does AI in Retail Marketing and eCommerce Work?

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AI was just a philosophical concept until the late 20th century when researchers introduced methodologies to make it real. AI has been around in retail marketing, mostly to reduce the tedious work of remembering all the finances. Traditional shops used to maintain a list of loyal customers too. Shops were on their way to going digital long before the pandemic, but the sudden shift to online buying and increased digital transactions caught many by surprise. The physical retail stores experienced most of the trauma. The pandemic disrupted the supply chains from all over the world.


Changes Go Far Beyond Just AI, Machine Learning

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SambaNova Systems is a technology startup founded in 2017 by a group of far-sighted engineers and data scientists who saw that the current approaches to AI and machine learning were beginning to run out of steam, and that an entire new architecture would be necessary in order to make AI accessible for everyone as well as deliver the scale, performance, accuracy and ease of use needed for future applications. AI and machine learning in particular have grown over the past decade to become key tools for processing and making sense of large and complex data sets. This trend is set to continue, with IDC forecasting that the overall AI software market will approach $240 billion in revenue in 2024, up from $156 billion in 2020. But AI is no longer just for supercomputing. The volumes of data collected by organizations have become large and complex data sets, leading to machine learning being incorporated into all manner of applications from natural language processing (NLP), high-resolution computer vision, recommendations and high performance computing (HPC) to everyday business processes.


Global Artificial Intelligence in IoT Market : IBM, Microsoft, Google, PTC, AWS, Oracle, GE, Salesforce, SAP, Hitachi, etc. – The Bisouv Network

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Gauging through Scope: Global Artificial Intelligence in IoT Market, 2020-26 A new report defining the global Artificial Intelligence in IoT market offers readers with vivid details on current and most recent industry developments along with futuristic predictions that allow players to recognize exact vendor initiatives, end-user preferences and purchase decisions along with profitability. The report delivers pertinent details on strategic planning and tactical business decisions that influence and stabilize growth prognosis in global Artificial Intelligence in IoT market. The report in its opening section introduces the global Artificial Intelligence in IoT market, featuring market definitions, overview, classification, segmentation, inclusive of market type and applications followed by product specifications, manufacturing initiatives,pricing structures, raw material sourcing and the like. Following this, the report also focuses and analyzes the main regional market conditions followed by a global assessment. Vendor Landscape The report draws references of an extensive analysis of the Artificial Intelligence in IoT market, entailing crucial details about key market players, complete with a broad overview of expansion probability and expansion strategies.


BBVA taps Google Cloud Chronicle to build AI security platform

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In conversation with Álvaro Garrido, chief security officer at BBVA, Finextra learns that the bank will collaborate with Google Cloud to adopt more advanced technology by placing it in a more cost-effective environment, with greater scalability. Garrido explains that after three years of investing heavily in security and working towards becoming a data-driven bank, now is a good time for BBVA to fully reap the benefits of advanced analytics. "We are getting to the point where we need to monitor more, detect better and react faster. I think these are the three components of not only BBVA's security agenda, but what allows cooperation in the financial industry," Garrido says. Mentioning Google Cloud's Network Telemetry and the ability to identify access patterns that may pose security or operational risks in real-time across a number of devices, he adds that the bank will be able to prevent threats "across the security chain - from the traditional computer space or in the IoT. It's the number of devices, [as well as] the granularity and the level of depth of what we monitor."


Project-Based Learning

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Did you know Education Ecosystem is like GitHub on video for developers? It is project-based learning ecosystem that teaches you how to build products using real project examples in fields of AI, programming, data science, design, game development, cryptocurrency and cybersecurity.


Case studies of successful AI startups

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With tech giants pouring billions of dollars into artificial intelligence projects, it's hard to see how startups can find their place and create successful business models that leverage AI. However, while fiercely competitive, the AI space is also constantly causing fundamental shifts in many sectors. And this creates the perfect environment for fast-thinking and -moving startups to carve a niche for themselves before the big players move in. Last week, technology analysis firm CB Insights published an update on the status of its list of top 100 AI startups of 2020 (in case you don't know, CB Insight publishes a list of 100 most promising AI startups every year). Out of the hundred startups, four have made exits, with three going public and one being acquired by Facebook.


How to Kickstart an AI Venture Without Proprietary Data

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A few years ago, I learned about the billions of dollars banks lose to credit card fraud on an annual basis. Better detection or prediction of fraud would be incredibly valuable. And so I considered the possibility of convincing a bank to share their transactional data in the hope of building a better fraud detection algorithm. The catch, unsurprisingly, was that no major bank is willing to share such data. They feel they're better off hiring a team of data scientists to work on the problem internally. My startup idea died a quick death.


Regulators and decisionmakers still don't 'get' AI technology

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Looking at how governments worldwide are dealing with tech giants, it becomes clearer that both sides do not necessarily speak the same language. While artificial intelligence (AI) developers have the information and the grasp of the technology, this does not extend to the regulators who sometimes have to police them. How can one regulate something one does not fully comprehend? It is a pickle, but fortunately the upside is that a consensus has started to form around the impact that AI will have on humankind and civil society at large. In fact, the public and private sectors are stepping up their requests for accountability and trust-building.


Featurespace Touts New Anti-Fraud System

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U.K.-based Featurespace, which offers anti-fraud systems for financial institutions (FIs), on Thursday (Feb. In a press release, the company said the new product, intended for the card and payments industry, provides a "deeper layer of defense to protect consumers from scams, account takeover, card and payments fraud, which cost an estimated $42 billion in 2020." The new product is "truly the next generation of machine learning," said Dave Excell, founder of Featurespace. The company said that it involves "a breakthrough in deep learning technology" that is capable of pinpointing potential fraud before the victim's money is removed from their account. That serves as "the best line of defense against scams, account takeover, card and payment fraud attacks," the release stated.