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Arm introduced the Armv9 architecture in response to the global demand for ubiquitous specialized processing with increasingly capable security and artificial intelligence (AI). Armv9 is the first new Arm architecture in a decade, building on the success of Armv8.

The new capabilities in Armv9 are designed to accelerate the move from general-purpose to more specialized compute across every application as AI, the Internet of Things (IoT) and 5G gain momentum globally.

To address the greatest technology challenge today securing the worlds data the Armv9 roadmap introduces the Arm Confidential Compute Architecture (CCA). Confidential computing shields portions of code and data from access or modification while in-use, even from privileged software, by performing computation in a hardware-based secure environment.

The Arm CCA will introduce the concept of dynamically created Realms, useable by all applications, in a region that is separate from both the secure and non-secure worlds. For example, in business applications, Realms can protect commercially sensitive data and code from the rest of the system while it is in-use, at rest, and in transit.

The ubiquity and range of AI workloads demands more diverse and specialized solutions. For example, it is estimated there will be more than eight billion AI-enabled voice-assisted devices in use by the mid-2020s, and 90 percent or more of on-device applications will contain AI elements along with AI-based interfaces, like vision or voice.

To address this need, Arm partnered with Fujitsu to create the Scalable Vector Extension (SVE) technology, which is at the heart of Fugaku, the worlds fastest supercomputer. Building on that work, Arm has developed SVE2 for Armv9 to enable enhanced machine learning (ML) and digital signal processing (DSP) capabilities across a wider range of applications.

SVE2 enhances the processing ability of 5G systems, virtual and augmented reality, and ML workloads running locally on CPUs, such as image processing and smart home applications. Over the next few years, Arm will further extend the AI capabilities of its technology with substantial enhancements in matrix multiplication within the CPU, in addition to ongoing AI innovations in its Mali GPUs and Ethos NPUs.

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A Solution for the Future Needs of artificial intelligence - ARC Viewpoints

Non-disclosure agreements (NDAs) are some of the most commonly drafted agreements at any company. While they may be common, however, that doesnt mean theyre unimportant in fact, theyre critical to protecting a companys business strategies and trade secrets.

Most companies use the same form NDA in almost every situation, changing only party names and the description of the confidential information involved, leaving the rest of the agreement to a series of standard terms. This means that, even though theyre important, NDAs are very repetitive and routine in terms of drafting.

Corporate legal departments have long been bogged down in routine contracts. Preparing NDAs can take up a significant amount of lawyers time, taking them away from other important work that can bring more value to the organization.

The routine nature of NDAs makes them a prime candidate for contract artificial intelligence. With the combination of AI and contracts, business users can engage in risk-free self-service to review and redline NDAs in less than two minutes. This frees up your legal staff to focus on higher-value work that helps support and grow the business.

AI is changing the game when it comes to routine contracts like NDAs. With AI, you can increase the speed of contract preparation and review while at the same time reducing your risk.

Onits ReviewAI software employs AI to quickly and accurately draft, review, redline, and edit all types of contracts, including NDAs, in a matter of minutes. ReviewAI isnt just for those with legal training non-legal business users can use ReviewAI to receive reviewed, redlined, and approved NDAs via email or a self-service portal in less than two minutes. This self-service option removes a huge burden from legals shoulders, freeing up valuable time for more complex legal matters.

For lawyers and contract professionals working on NDAs, ReviewAI offers a Word add-in that offers more hands-on functionality. The add-in automatically drafts, reviews, redlines and edits your NDAs against corporate standards. Youve likely invested time in crafting standardized language for your NDAs and defining exactly what constitutes confidential information and how its to be treated. ReviewAI will learn those terms and customize them based on user feedback, making your NDA applicable to whatever scenario youre addressing at a given moment.

ReviewAI is a game-changer because it contains NDA automation. The software empowers legal departments to review contracts 60-70% faster. It also leads to a 51.5% increase in user productivity, which is critical for making the most of your resources at a time when legal departments are under increased pressure to do more with less. With Review AI, it takes two minutes or less to review and redline a contract and also offers:

ReviewAI handles the entire pre-signature phase for NDAs. This dramatically reduces your contract lead time while decreasing your legal costs.

NDAs and other routine, repetitive contracts shouldnt take attorney time and focus away from higher-value legal work. Tools that combine AI and contracts to produce NDA automation take these time-consuming tasks off your lawyers plates and also empower your business users to engage in self-service without increasing risk.

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NDA Automation: Get Better, Faster NDAs With the Help of Artificial Intelligence - JD Supra

AI will shift tasks around,

Well, is artificial intelligence a job-killer or not? We keep hearing both sides, from projections of doom for many professions that will necessitate things such as universal basic income to help sidelined workers, to projections of countless unfilled jobs needed to build and manage AI-powered enterprises. For a worker losing his or her job to automation, knowing that an AI programming job is being created elsewhere is of little solace.

Perhaps the reality will be somewhere in between. An MIT report released at the end of last year states recent fears about AI leading to mass unemployment are unlikely to be realized. Instead, we believe thatlike all previous labor-saving technologiesAI will enable new industries to emerge, creating more new jobs than are lost to the technology, the reports authors, led by Thomas Malone, director of the MIT Center for Collective Intelligence, conclude. But we see a significant need for governments and other parts of society to help smooth this transition, especially for the individuals whose old jobs are disrupted and who cannot easily find new ones.

The future of AI and job growth or losses may be nuanced, a recent report from BCG and Faethm suggests. Though these technologies will eliminate some jobs, they will create many others, the reports team of authors, led by BCGs Rainer Strack. Governments, companies, and individuals all need to understand these shifts when they plan for the future.

What needs to be understood? For starters, the net number of jobs lost or gained is an artificially simple metric to gauge the impact of digitization, Strack and his co-authors state. For example, eliminating 10 million jobs and creating 10 million new jobs would appear to have negligible impact. In fact, however, doing so would represent a huge economic disruption for the countrynot to mention for the millions of people with their jobs at stake.

Theres even a paradox in play. Computers tend to perform well in tasks that humans find difficult or time-consuming to do, but they tend to work less effectively in tasks that humans find easy to do, the report notes. Also, in many areas, technologies will improve the quality of work that humans do by allowing them to focus on more strategic, value-creating, and personally rewarding tasks.

In other words, AI cant take over many of the soft skills essential to businesses growth initiative, intuition, passion, and ability to sell ideas and concepts. Add that to more technical abilities needed to build and maintain AI and digital environments and keep them focused on what the business needs. In many sectors, severe shortages of skilled workers will mean that growth in demand for talent will be unmet, Strack and his co-authors state. This is particularly true for computer-related occupations and jobs in science, technology, engineering, and math, since technology is fueling the rise of automation across all industries. This is why the computer and mathematics job family group is likely to suffer by far the greatest worker deficits.

At the same time, there will also be increasing demand for jobs requiring compassionate human contact, such as health care, social services, and teaching, they add.

Along with the BCG-Faethms observations, it should be noted that AI cannot replicate the entrepreneurial skills that will be pulling together technology solutions and platforms to connect to the needs of markets. Humans are the innovators.

What to do? Strack and his team urge people to take charge of their professional development through lifelong learning. Individuals will have to take greater responsibility for their own professional development, whether that means through upskilling or reskilling, they state. Pay attention to sources of information and update skills accordingly, either by searching out high-quality providers of education or by charting your own course amid the vast amount of online-learning offers.

The BCG-Faethm team also makes the following recommendations from a corporate perspective:

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Artificial Intelligences Impact On Jobs Is Nuanced - Forbes

Could artificial intelligence reduce the need for human therapists?

Websites, smartphone apps and social-media sites are dispensing mental-health advice, often using artificial intelligence. Meanwhile, clinicians and researchers are looking to AI to help define mental illness more objectively, identify high-risk people and ensure quality of care.

Some experts believe AI can make treatment more accessible and affordable. There has long been a severe shortage of mental-health professionals, and since the Covid pandemic, the need for support is greater than ever. For instance, users can have conversations with AI-powered chatbots, allowing them to get help anytime, anywhere, often for less money than traditional therapy.

The algorithms underpinning these endeavors learn by combing through large amounts of data generated from social-media posts, smartphone data, electronic health records, therapy-session transcripts, brain scans and other sources to identify patterns that are difficult for humans to discern.

Despite the promise, there are some big concerns. The efficacy of some products is questionable, a problem only made worse by the fact that private companies dont always share information about how their AI works. Problems about accuracy raise concerns about amplifying bad advice to people who may be vulnerable or incapable of critical thinking, as well as fears of perpetuating racial or cultural biases. Concerns also persist about private information being shared in unexpected ways or with unintended parties.

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Can Artificial Intelligence Replace Human Therapists? - The Wall Street Journal

The Energy Department, in all aspects of its work, is turning to artificial intelligence to accelerate its output.

DOEs Office of Cybersecurity, Energy Security, and Emergency Response (CESER) is using artificial intelligence to monitor threats to the electric grid. Its inspector general is looking at AI to flag potential fraud.

Fred Streitz, the chief AI scientist in DOEs Artificial Intelligence and Technology Office, said all of the agencys offices are using AI at some level, and said the use cases are getting more advanced.

Its going to touch everything, in the same way that electricity now touches everything that happens. We believe that AI is going to wind up touching, in some way or another, almost every aspect of our lives going forward, Streitz said last week at an AI conference hosted by the National Defense Industrial Association.

Irene Qualters, the associate lab director for simulation & computation at DOEs Los Alamos National Laboratory, said the lab is working to harden AI algorithms against threats, improving the explainability of AI-produced results and quantifying the certainty AI models have in making predictions.

The lab is also looking at AIs usefulness to study climate and natural disasters.

AI is opening a whole new avenue of exploration and understanding, Qualters said.

DOEs AI and high-performance capabilities factored heavily into the Trump administrations early response to the COVID-19 pandemic. The White House launched a COVID-19 High-Performance Computing Consortiumin March 2020 to give coronavirus researchers access to the worlds most powerful supercomputers.

But as DOE weaves AI into all aspects of its mission, the stakes become higher, and the need to ensure AI-powered work is transparent and reliable becomes greater. The National Nuclear Security Administration, for example, uses AI to assess data as part of its non-proliferation work.

Increasing use of AI in mission-critical areas where there are real-world consequences, we are working toward that. Its a direction we need to go because of the inherent advantages of using these AI technologies to exactly do something like create a more resilient grid, but trustworthiness is an important component of that, and thats another piece of research thats being done actively, Streitz said.

While DOE employs more than 10,000 scientists and engineers, Streitz said that the workforce only accounts for a fraction of the brainpower on AI research in the U.S. The agency, he added, relies on collaboration with other federal science agencies and the private sector.

Qualters said DOEs AI research in some cases focuses heavily on infrastructure use cases, while the National Science Foundation supports some of the fundamental research behind AI.

NSF and the Army Research Office, for example, supported recent research at Carnegie Mellon University that pitted an AI program against six professional players in a game of poker.

Streitz said AIs aptitude at poker, compared to its master of games like chess, marks a paradigm shift in the sophistication of these algorithms.

You cant just play the cards youre dealt, you have to change your odds, and that means bluffing. But what is bluffing at the end of the day? Bluffing is lying. You have to pretend that you have cards you dont have. And the notion that we can actually teach a computer how to do that it understands that there are situations when it knows perfectly well what cards it has, and it knows what all the odds are, and it simply decides, now is a good time to fake it thats really a fundamental difference from, for instance, chess, he said.

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Its going to touch everything. Energy Department weaves AI into mission-critical work - Federal News Network