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DUBLIN, March 31, 2021 /PRNewswire/ -- The "Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2020" report has been added to ResearchAndMarkets.com's offering.

This report contains a comprehensive listing of all artificial intelligence partnering deals announced since 2010 including financial terms where available including over 440 links to online deal records of actual artificial intelligence partnering deals as disclosed by the deal parties.

The report provides a detailed understanding and analysis of how and why companies enter artificial intelligencepartnering deals. The majority of deals are early development stage whereby the licensee obtains a right or an option right to license the licensors artificial intelligencetechnology or product candidates. These deals tend to be multicomponent, starting with collaborative R&D, and commercialization of outcomes.

This report provides details of the latest artificial intelligence, oligonucletides including aptamers agreements announced in the healthcare sectors.

Understanding the flexibility of a prospective partner's negotiated deals terms provides critical insight into the negotiation process in terms of what you can expect to achieve during the negotiation of terms. Whilst many smaller companies will be seeking details of the payments clauses, the devil is in the detail in terms of how payments are triggered - contract documents provide this insight where press releases and databases do not.

In addition, where available, records include contract documents as submitted to the Securities Exchange Commission by companies and their partners.

Contract documents provide the answers to numerous questions about a prospective partner's flexibility on a wide range of important issues, many of which will have a significant impact on each party's ability to derive value from the deal.

In addition, a comprehensive appendix is provided organized by artificial intelligence partnering company A-Z, deal type definitions and artificial intelligence partnering agreements example. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

The report also includes numerous tables and figures that illustrate the trends and activities in artificial intelligence partnering and dealmaking since 2010.

In conclusion, this report provides everything a prospective dealmaker needs to know about partnering in the research, development and commercialization of artificial intelligence technologies and products.

Report scope

Analyzing actual company deals and agreements allows assessment of the following:

Global Artificial Intelligence Partnering Terms and Agreements includes:

In Global Artificial Intelligence Partnering Terms and Agreements, the available contracts are listed by:

Key Topics Covered:

Executive Summary

Chapter 1 - Introduction

Chapter 2 - Trends in artificial intelligence dealmaking2.1. Introduction2.2. Artificial intelligence partnering over the years2.3. Most active artificial intelligence dealmakers2.4. Artificial intelligence partnering by deal type2.5. Artificial intelligence partnering by therapy area2.6. Deal terms for artificial intelligence partnering

Chapter 3 - Leading artificial intelligence deals3.1. Introduction3.2. Top artificial intelligence deals by value

Chapter 4 - Most active artificial intelligence dealmakers4.1. Introduction4.2. Most active artificial intelligence dealmakers4.3. Most active artificial intelligence partnering company profiles

Chapter 5 - Artificial intelligence contracts dealmaking directory5.1. Introduction5.2. Artificial intelligence contracts dealmaking directory

Chapter 6 - Artificial intelligence dealmaking by technology type

Chapter 7 - Partnering resource center7.1. Online partnering7.2. Partnering events7.3. Further reading on dealmaking

Appendices

For more information about this report visit https://www.researchandmarkets.com/r/ze6mu2

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Read more from the original source:
Global Healthcare Artificial Intelligence (AI) Deals Report 2020: Details of the Latest AI Deals, Oligonucletides Including Aptamers Agreements...

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.

Go here to see the original:
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.

Continue reading here:
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:

Read more:
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.

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