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Democratic Rep. Alexandria Ocasio-Cortez of New York at a press conference on Capitol Hill on April 7, 2022.Kevin Dietsch/Getty Images

AOC slammed top Democrats for backing Rep. Henry Cuellar, an anti-abortion Democrat with an A rating from the NRA.

Cuellar faced a primary challenge from progressive Jessica Cisneros, but leads her by less than 200 votes.

"This was an utter failure of leadership," said AOC. "Congress should not be an incumbent protection racket."

Democratic Rep. Alexandria Ocasio-Cortez of New York laced into top House Democrats late on Tuesday night, condemning them for working to bolster conservative Democratic Rep. Henry Cuellar of Texas over a progressive challenger.

"Accountability isn't partisan. This was an utter failure of leadership," Ocasio-Cortez wrote on Twitter. "Congress should not be an incumbent protection racket and sadly it is treated as such by far too many."

Cuellar, the only House Democrat with an "A" rating from the National Rifle Association and the only House Democrat to vote against a bill that would codify abortion rights into law, faced a primary challenge from progressive lawyer Jessica Cisneros. As of Wednesday morning, the incumbent congressman led Cisneros by less than 200 votes.

But despite his conspicuous break from major party priorities, top Democrats held fundraisers and recorded robo-calls on behalf of Cuellar. That support became even more notable as aleaked draft Supreme Court opinion indicated that Roe v. Wade was likely to be overturned, and two mass shootings took place in Buffalo, New York and Uvalde, Texas.

Adding to the drama, Cuellar's home and campaign office were raided by the FBI in January, though his lawyer says that the congressman is not the subject of the investigation.

"On the day of a mass shooting and weeks after news of Roe, Democratic Party leadership rallied for a pro-NRA, anti-choice incumbent under investigation in a close primary," Ocasio-Cortez wrote. "Robocalls, fundraisers, all of it."

Top Democrats had defended their support for Cuellar in light of the leaked abortion ruling. House Democratic Majority Leader Steny Hoyer told Insider earlier this month that the Democratic Party is a "diverse party" with "diverse opinions," while House Speaker Nancy Pelosi defended him as a "valued member of our caucus."

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"The fact is those who fail their communities deserve to lose," Ocasio-Cortez said. "They don't need rescuing from powerful leaders who state they fight for gun safety, the right to choose, and more."

The New York congresswoman and other top progressives including Sen. Elizabeth Warren of Massachusetts and Rep. Pramila Jayapal of Washington had backed Cisneros, who was challenging Cuellar for the second time. And Cisneros had called on Democratic leaders to drop their support for Cuellar in light of the leaked abortion opinion.

Noting that the run-off was "extremely close," Ocasio-Cortez argued that Democratic leaders had "gone to the mat for a pro-NRA incumbent" and will have "mobilized against a badly needed grassroots" ahead of the 2022 midterm elections.

She also noted that Cuellar was a member of the "Unbreakable Nine," a group of conservative House Democrats who demanded that the bipartisan infrastructure law be passed separately from the now-doomed "Build Back Better" social spending bill, which ultimately imperiled the expanded child tax credit that was set to be renewed as part of the legislation.

"We can't afford to reward such acts," she concluded. "We can do better."

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AOC denounces top Democrats for supporting an anti-abortion congressman with an 'A' rating from the NRA on the heels of two mass shootings and news of...

Artificial intelligence (AI) is on the priority list for every executive who uses technology to enable their business. And today, every business is a technology business. Despite the excitement around AI and investments in its capabilities, only about a third of companiessay theyve adopted leading operational practices for AI but an increasing percentage are working toward that goal.

While AI is often seen as the golden ticket to take business operations into the 21st century and it can to do so, the technology must be approached specifically and strategically, not as an all-in-one solution.

In the universe of technology, one can picture a solar system of interdependent capabilities. At the core, cloud technology serves as the sun a central power source fuelling and enabling other technologies. Underlying cloud platforms, such as Amazon Web Services or Google Cloud, provide the basis for other capabilities to flourish in the technology universe.

Rotating around cloud platforms, there are various AI planets in orbit that build off of cloud infrastructure to deliver solutions such as automation, machine learning, robotic process automation, and more. Many business leaders are eager to enter the orbit of artificial intelligence solutions, but must first start by building the necessary foundation for successful AI implementations.

Once the centre of the AI solar system is in place, to effectively unlock the power of AI, its important that business leaders understand what it is they are trying to solve. And while many suppliers have powerful offerings, AI is not one-size-fits-all in its approach or implementation. It takes several capabilities and applications to drive true end-to-end AI outcomes.

This ecosystem strategy can ultimately offer flexibility and stability for IT decision-makers looking to harness business data and drive meaningful results for their organisations. Key to demonstrating the importance of AI ecosystems is discussing current barriers a company is trying to overcome and what specific AI capabilities will solve for them.

Today, business leaders are looking to define the function of artificial intelligence in their organisations and how they can effectively implement AI given their current technology stacks.

For example, a banking executive may look to automate some of their companys digital banking capabilities. To get there, the institution must consider how they are currently housing their data, how that data will be processed and then refined for usage, and finally how the data can provide insight to their workforce and what insights will be most valuable to them.

In this case, an organisation may have to consider combining the technology and environment they have in place with new technology and capabilities to achieve their desired outcome of a new automated banking tool. The allure of a one-stop shop for AI needs may sway businesses to heavily invest in one provider, which can put up roadblocks on the journey to a meaningful, AI-powered solution.

Part of the trouble with seeing one supplier as a silver-bullet solution is that businesses may invest too heavily in a provider that wont help them move the needle on all of their specific AI goals. Given the hefty budgets businesses are developing for their IT departments, its critical to understand that investments are going towards the appropriate solution(s) and that more money towards a nebulous, blanket AI may not always equate to unlocking business success.

IT decision-makers must have a clear understanding of their companys technology solar system before implementing a new AI tool Anthony Ciarlo and Frank Farrell, Deloitte

Moreover, the overarching cloud environment in which an AI solution is deployed can make or break its success. This means IT decision-makers must have a clear understanding of their companys technology solar system before implementing a new AI tool. When AI-related requests for proposal come across our desks, our first goal is to work through the specific needs of the clients organisation and if the resources they are putting behind the AI solutions will get them where they want to be.

End to end, it is difficult for any one supplier to meet all of the AI needs of an organisation. Some are leaders in automation, while others are leaders in data analytics or machine learning understanding these different strengths enables Deloitte to provide meaningful, tailored assessments as to what investments should be made.

As a systems integrator, once the Deloitte team has holistic insight into an organisations pain points, it can provide confident recommendations as to where money should be invested and how companies can see the greatest return on investment in their technology budgets. The Deloitte team delivers confidence in integrating and navigating the solar system to provide the desired outcomes its clients and their clients need.

The ecosystem approach to AI solutions marks an important shift for how systems integrators should be approaching their client solutions. In years to come, its likely that there will be increased collaboration across market providers, resulting in more streamlined, transparent AI implementation processes.

The key driver for this shift is continued conversations with business and technology leaders who understand that AI is not an isolated entity, but rather serves as a key component within a solar system of interconnected platforms and tools that can offer individualised solutions for the most pressing business challenges.

Anthony Ciarlo is strategy and analytics alliances leader and Frank Farrell is principal for cloud analytics and AI ecosystems at Deloitte.

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How to leverage the artificial intelligence solar system - ComputerWeekly.com

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The United States spends more on health care than any other country in the world.

But Americans aren't as healthy as people living in other developed countries.

Could artificial intelligence change all that?

WBUR's On Point brings you Smarter health, a four-part series exploring how artificial intelligence and machine learning may revolutionize the health care industry.

We'll investigate the technology already available, or in development, for clinical settings, examine the ethical dilemmas the technology presents in medicine and understand the guiderails and regulations in progress to advise AI advancements.

We'll also hear from the people involved in AI in health care; scientists developing tools, clinicians and doctors using the tools, and patients experiencing changing technology as part of their care.

Episode 1. How AI is transforming health care: Artificial intelligence offers the potential to improve health care from predicting someones risk of having a heart attack, to predicting seizure loads for epilepsy patients, to solving public health problems. What is the potential for AI to transform American health care?

Episode 2. Ethics of the death predictor: We'll break down the ethical considerations of AI in health care.What are the privacy concerns about data collection, and how can researchers and developers advance tools while protecting patients?

Episode 3. Regulating the algorithm:As AI develops in the health care space,regulations need to develop in tandem. We'll talk to the head of the FDAsdigital health division, Dr. Matthew Diamond, about what role the FDA will play as AI expands. Well also talk to experts about guardrails needed to ensure patient safety and privacy.

Episode 4. The people of AI: Our final episode gets up close with the people working and developing AI technology, and the patients receiving AI care. How can this technology thrive in our complex and broken health care system?

Radio

Podcast

Got a question about how AI will impact how you receivehealth care? Or maybe you're a scientist, doctor or patient with an AI story to share? Leave us a voicemail at 617-353-0683.

Meghna Chakrabarti is the award-winning host and editor ofOn Point. Based in Boston, she is on the air Monday through Friday.

The Alliance for Women in Media honoredOn Point'sepisode"A Look Back at 1992 Los Angeles And America Since Rodney King"with a 2022 nationalGracie Award for Best News Documentary. The Alliance for Women in Media also gave Meghna anhonorable mentionfor best nationally syndicated non-commercial correspondent/host.

On Point'sepisode on Los Angeles since Rodney King also won a2022 regional Edward R. Murrow awardfor best news documentary. In 2021,On Pointwon aNational Edward R. Murrow awardfor best news documentary for"What the President Knew."The show examined presidential decision-making before 9/11 and the COVID pandemic.

Chakrabarti is the former host ofRadio Boston, WBURs acclaimed weekday local show. She's the former host ofModern Love: The Podcast, a collaboration of WBUR and The New York Times (2016-2020) and was the primary fill-in host forHere & Now, NPR and WBUR's midday show. She reported on New England transportation and energy issues for WBURs news department.

This series is supported in part by Vertex, The Science of Possibility.

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Smarter health: Artificial intelligence and the future of American health care - WBUR News

LONDON, May 24, 2022 (GLOBE NEWSWIRE) -- According to The Business Research Companys research report on the artificial intelligence (AI) in drug discovery market, the rising adoption of cloud-based applications and services by pharmaceutical companies will contribute to the growth of AI in the drug discovery market. Among the various end-users of cloud-based drug discovery platforms, pharmaceutical vendors are likely to be major stakeholders, holding a high-value share of the global cloud-based drug discovery platform market. An opportunity analysis of the global market reveals that leading software vendors have already adopted cloud-based drug discovery platforms to facilitate seamless research and development processes. Moreover, the cloud-based drug discovery platform revolution will witness significant growth in the coming years, thereby creating better opportunities for software vendors for growth and expansion. For example, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced in December 2021 that it is collaborating with Pfizer to develop innovative, cloud-based solutions that have the potential to improve how new medicines are developed, manufactured, and distributed for clinical trials. The companies are exploring these advances through their newly created Pfizer Amazon Collaboration Team (PACT) initiative, which applies AWS capabilities in analytics, machine learning, compute, storage, security, and cloud data warehousing to Pfizer laboratory, clinical manufacturing, and clinical supply chain efforts. Thus, the increasing adoption of cloud-based applications and services by pharmaceutical companies will contribute positively to the AI drug discovery market size.

Request for a sample of the global artificial intelligence (AI) in drug discovery market report

The global artificial intelligence in drug discovery market size is expected to grow from $0.79 billion in 2021 to $1.04 billion in 2022 at a compound annual growth rate (CAGR) of 31.6%. The growth in the market is mainly due to the companies resuming their operations and adapting to the new normal while recovering from the COVID-19 impact, which had earlier led to restrictive containment measures involving social distancing, remote working, and the closure of commercial activities that resulted in operational challenges. The AI in drug discovery market is expected to reach $2.99 billion in 2026 at a CAGR of 30.2%.

Use of AI through Machine Learning (ML) is a trend in assessing pre-clinical studies during the drug development process. Pre-clinical studies are non-clinical studies for novel drug substances to establish clinical efficacy and safety in a controlled environment before testing with a final target population. ML modelling pharmacokinetic (PK) and pharmacodynamic (PD) methodologies are applied in in-vitro and preclinical PK studies to successfully anticipate the dose concentration response relationship of pipeline assets. In addition, deep learning methodologies are employed as In-Silico methods for successfully predicting the therapeutic/pharmacological properties of novel molecules by utilizing transcriptomic data, which includes various biological systems and controlled conditions. Besides the drug discovery market, machine learning technology finds its application in the AI in medical diagnostics market as well as AI in medical imaging market.

Major players in the artificial intelligence for drug discovery and development market are IBM Corporation, Microsoft, Atomwise Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, Benevolent AI, Exscientia, Cyclica, and BIOAGE.

The global artificial intelligence in drug discovery market report is segmented by technology into deep learning, machine learning; by drug type into small molecule, large molecules; by disease type into metabolic disease, cardiovascular disease, oncology, neurodegenerative diseases, others; by end-users into pharmaceutical companies, biopharmaceutical companies, academic and research institutes, others.

In 2021, North America was the largest region in the artificial intelligence (AI) in drug discovery market. It was followed by the Asia-Pacific, Western Europe, and then the other regions. The regions covered in the AI in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, and Africa.

Artificial Intelligence (AI) In Drug Discovery Global Market Report 2022 Market Size, Trends, And Global Forecast 2022-2026 is one of a series of new reports from The Business Research Company that provide artificial intelligence (AI) in drug discovery market overviews, artificial intelligence (AI) in drug discovery market analyze and forecast market size and growth for the whole market, artificial intelligence (AI) in drug discovery market segments and geographies, artificial intelligence (AI) in drug discovery market trends, artificial intelligence (AI) in drug discovery market drivers, artificial intelligence (AI) in drug discovery market restraints, artificial intelligence (AI) in drug discovery market leading competitors revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.

The report also gives in-depth analysis of the impact of COVID-19 on the market. The reports draw on 150,000 datasets, extensive secondary research, and exclusive insights from interviews with industry leaders. A highly experienced and expert team of analysts and modelers provides market analysis and forecasts. The reports identify top countries and segments for opportunities and strategies based on market trends and leading competitors approaches.

Not the market you are looking for? Check out some similar market intelligence reports:

AI In Pharma Global Market Report 2022 By Technology (Context-Aware Processing, Natural Language Processing, Querying Method, Deep Learning), By Drug Type (Small Molecule, Large Molecules), By Application (Diagnosis, Clinical Trial Research, Drug Discovery, Research And Development, Epidemic Prediction) Market Size, Trends, And Global Forecast 2022-2026

Artificial Intelligence In Healthcare Global Market Report 2022 By Offering (Hardware, Software), By Algorithms (Deep Learning, Querying Method, Natural Language Processing, Context Aware Processing), By Application (Robot-Assisted Surgery, Virtual Nursing Assistant, Administrative Workflow Assistance, Fraud Detection, Dosage Error Reduction, Clinical Trial Participant Identifier, Preliminary Diagnosis), By End User(Hospitals And Diagnostic Centers, Pharmaceutical And Biopharmaceutical Companies, Healthcare Payers, Patients) Market Size, Trends, And Global Forecast 2022-2026

Cloud Services Global Market Report 2022 By Type (Software As A Service (SaaS), Platform As A Service (PaaS), Infrastructure As A Service (IaaS), Business Process As A Service (BPaaS)), By End-User Industry (BFSI, Media And Entertainment, IT And Telecommunications, Energy And Utilities, Government And Public Sector, Retail And Consumer Goods, Manufacturing), By Application (Storage, Backup, And Disaster Recovery, Application Development And Testing, Database Management, Business Analytics, Integration And Orchestration, Customer Relationship Management), By Deployment Model (Public Cloud, Private Cloud, Hybrid Cloud), By Organization Size (Large Enterprises, Small And Medium Enterprises) Market Size, Trends, And Global Forecast 2022-2026

Interested to know more about The Business Research Company?

The Business Research Company is a market intelligence firm that excels in company, market, and consumer research. Located globally it has specialist consultants in a wide range of industries including manufacturing, healthcare, financial services, chemicals, and technology.

The Worlds Most Comprehensive Database

The Business Research Companys flagship product, Global Market Model, is a market intelligence platform covering various macroeconomic indicators and metrics across 60 geographies and 27 industries. The Global Market Model covers multi-layered datasets which help its users assess supply-demand gaps.

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Artificial Intelligence (AI) In Drug Discovery Market Growth Is Driven At A 30% Rate With Increasing Adoption Of Cloud-Based Applications And Services...

Written by Suzanne Smalley May 25, 2022 | CYBERSCOOP

The U.S. militarys top expert on artificial intelligence (AI) said Wednesday that the Pentagon must up its game to ensure American supremacy in a future era where artificial intelligence will determine success on the battlefield.

China aims to dominate the world in the AI space by 2030, the Pentagons Joint Artificial Intelligence Director Lt. Gen. Michael Groen told an Atlantic Council-convened audience gathered for a discussion of AI in national security. Groen said that AI will be a $16 trillion industry by 2030, and will raise GDP significantly for both China and the U.S.

Groen said DOD must reinvent itself to meet the challenge, arguing that the Pentagon will need to do more to bring the branches together and act as a doer instead of a coordinating body. Citing Amazon founder Jeff Bezoss 2002 directive that all Amazon components must work with one organization-wide data set, Groen said that in the same way the Pentagon must lead its various components to be on more unified footing.

Its time for the Department of Defense to have a similar focus on using data to solve problems, to think about their problems through a data lens overcoming the cultural obstacles to actually become a competitive enterprise that can outfight any opponent and has the same level of productivity and efficiency that we desire for our taxpayers, Groen said. Clearly, the competition is around us.

Its time for the Department of Defense to have a similar focus on using data to solve problems, to think about their problems through a data lens overcoming the cultural obstacles to actually become a competitive enterprise that can outfight any opponent.

Acknowledging the difficulties inherent to adaptation for an agency bogged down by bureaucracy, Groen said he is focused on improving DODs efficiency as it seeks to take on the Chinese AI machine.

Implementation in the department, of course, is always a challenge as new technology meets legacy processes, legacy organizations and legacy technology, Groen said. Implementation, of course, is the key to successful transformation and implementation is extraordinarily challenging as artificial intelligence and related technologies cross cut not just service lines, but almost every procedural line or process line across the department.

Groen said China is now executing its 14th five-year plan to meet its goal for AI supremacy by 2030 while the U.S. is now building its 14th AI-based program objective memorandum (POM), which refers to how DOD allots future funding to meet its strategic objectives. Suggesting that the U.S. and China are locked in a neck at neck battle for AI dominance, Groen said, those dates, maybe uncomfortably, maybe comfortably, overlap to quite a degree.

Groens remarks were made at an event at which the Atlantic Councils Scowcroft Center for Strategy and Security unveiled a new report focused on artificial intelligence in national security and defense. The report warns that without intentional, coordinated, and immediate action, the United States risks falling behind competitors in the ability to harness game-winning technologies that will dominate the kinetic and non-kinetic battlefield of the future.

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Head of DOD artificial intelligence command warns Pentagon must improve to beat China on AI - CyberScoop