Artificial Human Beings: The Amazing Examples Of Robotic Humanoids And Digital Humans
Digital human beings are photorealistic digitized virtual versions of humans. Consider them avatars. While they don't necessarily have to be created in the likeness of a specific individual (they can be entirely unique), they do look and act like humans. Unlike digital assistants such as Alexa or Siri, these AI-powered virtual beings are designed to interact, sympathize, and have conversations just like a fellow human would. Here are a few digital human beings in development or at work today: Neons: AI-powered lifeforms created by Samsung’s STAR Labs and called Neons include unique personalities such as a banker, K-pop star, and yoga instructor. While the technology is still young, the company expects that, ultimately, Neons will be available on a subscription basis to provide services such as a customer service or concierge. Digital Pop Stars: In Japan, new pop stars are getting attention—and these pop stars are made of pixels. One of the band members of AKB48, Amy, is entirely digital and was made from borrowing features from the human artists in the group. Another Japanese artist, Hatsune Miku, is a virtual character from Crypton Future Media.
Edge computing enables near-real-time application engagements. While local computing is not new, edge computing has emerged because technologies, such as content delivery networks and local edge devices and gateways, can now aggregate IoT sensor and mobile device insights to enable on-demand actions where people and physical processes exist, need them, and benefit from them. Want to dramatically improve customer experience, employee experience, and business achievements? This is powerful empowerment. Edge computing architectures have three major building blocks. Edge computing varies across different solution use cases and value scenarios, so it's difficult to define just a single pattern for everyone. Forrester's research does find three general building blocks core to most scenarios: edge management layers, edge networks, and edge intelligence fabric software. Enterprise and government use cases and case studies of how your peers are empowering their customers and advancing their market value with these empowering technologies. Functions and components of edge computing and the vendor landscape across all industries and the services already offered.
It isn’t just the engineering team that should focus on developing the product offering or key consumer touchpoints. Employees across the organisation are valuable as they all interact with different stages of the customer journey, and can provide valuable insights into pain points. They are capable of delivering a constant flow of new ideas to improve the digital customer experience, asking what will help to add value for your customers while engineering teams actually integrate a process to make it a reality. It’s no longer about the waterfall approach of working in segments, but rather coming together as a collaborative business and empowering the devops team to make the technical decisions needed to make the ideas a reality. Never underestimate the importance of collaboration in innovation. Giving employees at all levels the opportunity to get involved with their own ideas, perhaps via collaborative brainstorming sessions with the engineering team, can mean the risk of analysis paralysis will be averted, as everyone is involved from the beginning. It is essential for the management team to provide employees with not only the opportunity to share their thoughts about ways to develop the business, but the training to help them use their data and technology to bring these ideas to life.
Bala is right to call out that one of the primary benefits of a serverless and "single-purpose microservices" is that "You can use the right tool for the right job rather than being constrained to one language, one framework or even one database." This is immensely freeing for developers, because now instead of writing monolithic applications that likely have very low utilization with spiky workloads, they can build microservices tied to ephemeral serverless functions. When the system is idle, it shuts down and costs nothing to run. Everyone wins. This also can make maintaining code more straightforward. For monolithic applications, updating code can present a major burden because of the difficulty inherent in covering all dependencies. As Ophir Gross has noted, "Spaghetti code is full of checks to see what interface version is being used and to make sure that the right code is executed. It's often disorganized and usually results in higher maintenance efforts as changes in code affect functionality in areas that are challenging to predict during development stages."
DDoS Attacks Nearly Double Between Q4 2018 and Q4 2019
DDoS attackers continued to leverage non-standard protocols for amplification attacks in the last quarter of 2019, researchers found. Adversaries have also adopted Apple Remote Management Service (ARMS), part of the Apple Remote Desktop (ARD) application for remote administration. This tactic was first spotted in June 2019; by October, attacks were widespread. The fourth quarter of 2019 brought multiple high-profile DDoS attacks, including threats against financial organizations in South Africa, Singapore, and nations across Scandinavia. DDoS attacks aimed to cause disruption for the United Kingdom's Labour party and also targeted Minecraft servers at the Vatican. In a more recent case, just last week the FBI warned of a potential DDoS attack targeting a state-level voter registration and information site. "This demonstrates that DDoS is still a common attack method among cybercriminals driven by ideological motives or seeking financial gain, and organizations should be prepared for such attacks and have a deep understanding of how they evolve," researchers said in a statement.
Keeping up with disruptors through hybrid integration
For consumers of the digital era, experience is everything. They expect newfound convenience and flexibility and will have no problem looking elsewhere if this cannot be provided. This begs the question: how can the traditional players hope to keep up if this is the case? However, things aren’t as complex as they seem. One reason these new companies can drive such positive results comes down to the fact there is no reliance on legacy databases, and they can take advantage of existing third-party systems. For example, Citymapper leverages open data from the Transport of London to retrieve journey information and provide real-time visibility over transport schedules, allowing customers to make the best choice of journey based on timings. Meanwhile, Uber uses Google’s APIs to run their mapping software and match customers with the drivers closest to them. From there, the data is stored and used to predict supply and demand, as well as set fares. In both cases, these services have been built on existing integrations, meaning they don’t run into the same problems as many of the established players.
What Does Facebook's Quite AI Acquisitions Across UK Signify?
Amid all the controversies and roadblocks in its strive to attain AI leadership, the company is moving forward with innovation and tech developments. These developments are a major result of its acquisitions; small but significant. Facebook’s M&A activities are proving to be quite beneficial in its AI journey. Recently, the company acquired Scape Technologies which is a London-based computer vision startup working on location accuracy beyond the capabilities of GPS. Full terms of the deal remain as yet unknown, although a Companies House update reveals that Facebook Inc. now has majority control of the company (more than 75%). Further, a regulatory filings show that Scape’s previous venture capital representatives have resigned from the Scape board and are replaced by two Facebook executives. ... Meanwhile, the acquisition by Facebook, no matter what form it takes, looks like a good fit given the US company’s investment in next-generation platforms, including VR and AR. It is also another — perhaps, worrying — example of US tech companies hoovering up UK machine learning and AI talent early.
Why AI systems should be recognized as inventors
It’s important to note that the Artificial Inventor Project doesn’t want AI systems to own the patents for their creations. Such an interpretation of the case confuses ownership of patent rights with inventorship. Hence the DABUS applications list the AI as the inventor, with the AI’s owner listed as the patent applicant and prospective owner of any issued patents. It will be many years before they learn the full outcome of their applications. The team is appealing the rulings of both the EPO and the UK IPO. Other decisions in jurisdictions including the US, Germany, Israel, Taiwan, China, Korea are still pending, as well as one filed under the Patent Cooperation Treaty, which facilities the patent application process in more than 150 states. The World Intellectual Property Organization and the United States Patent and Trademark Office, meanwhile, have both requested comments on how they could develop policies for such applications. They may need to address any ambiguity over who owns the patents for AI-generated inventions when both the creator of the system and an individual user have contributed to its output. But granting ownership to the person who made the AI operable may be the most straightforward solution.
Mac attacks on the rise
"We saw a significant rise in the overall prevalence of Mac threats in 2019, with an increase of over 400% from 2018,'' the report by Malwarebytes Labs stated. Part of that increase can be attributed to an increase in its Malwarebytes for Mac user base, the report noted. To see if that increase reflected what was actually happening in the Mac threat landscape, Malwarebytes said, it examined threats per endpoint on both Macs and Windows PCs. "In 2019, we detected an average of 11 threats per Mac endpoint--nearly double the average of 5.8 threats per endpoint on Windows,'' the report said. Another key finding was that overall, consumer threat detections were down by 2% from 2018, but business detections increased by 13% in 2019, the report said. This resulted in a mere 1% increase in threat volume year-over-year. The sophistication of threat capabilities in 2019 increased, with many using exploits, credential stealing tools, and multi-stage attacks involving mass infections of a target, the report said. While seven of 10 top consumer threat categories decreased in volume, HackTools--a threat category for tools used to hack into systems and computers--increased against consumers by 42% year-over-year, bolstered by families such as MimiKatz, which also targeted businesses, the report said.
4 principles of analytics you cannot ignore
Data are a resource. If you are not analyzing it, it is an unused resource. At SAS, we often say, “Data without analytics is value not yet realized.” Naturally, then, wherever there is data, there needs to be analytics. But what does that mean today when we are generating more data and more diverse data than ever before? And all of that data streams or moves about many different networks. The first principle of analytics is about bringing the right analytics technology to the right place at the right time. Whether your data are on-premises, in a public or private cloud, or at the edges of the network – analytics needs to be there with it. ... You should pay great attention to the quality, robustness and performance of your algorithms. But the value of analytics is not in the features and functions of the algorithm – not anymore. The value is in solving data-driven business problems. The analytics platform is a commodity – everybody has algorithms. But operationalizing analytics is not a commodity. Everybody is challenged with bringing analytics to life. When you deploy analytics in production, it drives value and decisions.
Quote for the day:
"To be able to lead others, a man must be willing to go forward alone." -- Harry Truman
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