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Forget Nvidia: Billionaires Are Selling It and Buying These 2 Hypergrowth Artificial Intelligence (AI) Stocks Instead
For the better part of three decades, there has been no shortage of next-big-thing investments that have captivated the attention of professional and everyday investors. Since the advent of the internet completely changed the course of business in the mid-1990s, there’s nothing that’s garnered as much buzz on Wall Street as the artificial intelligence (AI) revolution.
With AI and the incorporation of machine learning (ML), software and systems have the ability to learn over time and become more proficient at their tasks. The broad-reaching scope of AI in virtually every sector and industry is why the analysts at PwC believe it could add more than $15 trillion to global gross domestic product by the turn of the decade.
Although dozens of stocks have benefited from the AI revolution, none have enjoyed a more direct boost to their sales and bottom line than semiconductor stock Nvidia (NASDAQ: NVDA).
This “infrastructure backbone” of the AI revolution is on the chopping block by billionaires
In a little more than a year, Nvidia has become what I like to call the “infrastructure backbone” of the AI movement. The company’s A100 and H100 graphics processing units (GPUs) have come to dominate high-compute data centers. Though estimates vary, Nvidia’s ultra-fast GPUs might account for 90% (or more) of the GPUs deployed in AI-accelerated data centers this year.
This is a company that’s also enjoying otherworldly pricing power on its GPUs. With demand overwhelming supply throughout 2023, cost of revenue moved only modestly higher while data center sales more than tripled. This is a pretty clear indication that pricing power is behind much of Nvidia’s sales and profit spike.
But not everyone is convinced that Nvidia is headed higher. During the December-ended quarter, eight prominent billionaire investors pared down their stakes in this top-performing megacap, including (total shares sold in parenthesis):
Israel Englander of Millennium Management (1,689,322 shares)
Jeff Yass of Susquehanna International (1,170,611 shares)
Steven Cohen of Point72 Asset Management (1,088,821 shares)
David Tepper of Appaloosa Management (235,000 shares)
Philippe Laffont of Coatue Management (218,839 shares)
Chase Coleman of Tiger Global Management (142,900 shares)
David Siegel and John Overdeck of Two Sigma Investments (30,663 shares)
One of the primary reasons to be skeptical of Nvidia’s phenomenal run-up is that it’s been driven by GPU scarcity. With Nvidia set to meaningfully increase its output in the current calendar year, and competitors like Advanced Micro Devices and Intel rolling out advanced AI-GPUs of their own, it’s only logical to expect its pricing power to decline.
What’s arguably even more concerning is that Nvidia’s top four customers by revenue (40% of total sales) are all developing AI-GPUs of their own. This is either going to lessen their future reliance on Nvidia as their in-house data center chips complement what Nvidia produces, or they could phase Nvidia’s infrastructure out altogether. Either way, it’s a worrisome development for a richly valued stock.
But while billionaires were busy running for the exit from Nvidia, they weren’t shy about pressing the buy button on two other hypergrowth AI stocks during the fourth quarter.
CrowdStrike Holdings
The first high-octane AI growth stock that appeared to whet the whistles of billionaire money managers during the December-ended quarter is cybersecurity company CrowdStrike Holdings (NASDAQ: CRWD). Four highly successful billionaires added to their funds’ respective stakes in CrowdStrike, including (total shares purchased in parenthesis):
Jeff Yass of Susquehanna International (400,988 shares)
Jim Simons of Renaissance Technologies (97,900 shares)
David Siegel and John Overdeck of Two Sigma Investments (91,091 shares)
On a macro basis, the cybersecurity industry has the look of a surefire growth story through at least the remainder of the decade. As businesses continue shifting their data online and into the cloud, third-party providers are being relied on with frequency to protect this information from hackers.
Furthermore, cybersecurity solutions can thrive in any economic climate. A bad day for Wall Street or a rough patch for the U.S. economy doesn’t mean a thing to hackers and robots looking to steal sensitive information. Since CrowdStrike is a subscription-driven company that protects end users, it’s well-positioned to generate predictable cash flow no matter what’s happening with the economy or stock market.
On a more company-specific basis, CrowdStrike brings clearly identifiable competitive advantages to the table for its customers and investors. The company’s Falcon security platform is driven by AI and ML. Falcon is overseeing trillions of events each week, which are making it smarter and more effective at recognizing and responding to potential threats.
There are a couple of key performance indicators that demonstrate just how much pull CrowdStrike has with businesses. Even though its platform isn’t the cheapest, gross retention rate has been pegged right around 98% for multiple years. Additionally, the company’s net retention rate hasn’t fallen below 119% in more than five years. This means the company’s existing clients are spending at least 19% more on a year-over-year basis.
But the key to CrowdStrike’s success has been its ability to upsell existing customers. Whereas a single-digit percentage of its clients seven years ago had purchased four or more cloud module subscriptions, 64% of its customers now have five or more cloud module subscriptions. These add-on sales have lifted its adjusted subscription gross margin to an impressive 80%!
Snowflake
The second hypergrowth artificial intelligence stock that billionaires were buying as they were sending Nvidia to the chopping block during the December-ended quarter is cloud data-warehousing company Snowflake (NYSE: SNOW). Similar to CrowdStrike, four billionaire investors stepped up and added to their funds’ stakes, including (total shares purchased in parenthesis):
Ken Griffin of Citadel Advisors (1,985,426 shares)
David Siegel and John Overdeck of Two Sigma Investments (1,204,387 shares)
Israel Englander of Millennium Management (888,047 shares)
There look to be two reasons why billionaire asset managers are choosing to load up on shares of Snowflake: opportunity and competitive edge.
With regard to the former, enterprise cloud spending, and AI solutions/applications within the cloud, are still in their early innings of expansion. Buying shares of Snowflake offers a way for investors to have exposure to the rapid growth in enterprise cloud and AI.
The other reason billionaires likely piled into Snowflake is because of its well-defined competitive advantages. For example, Snowflake’s infrastructure is layered atop the leading cloud infrastructure service platforms. While sharing data can be challenging across competing cloud platforms, it’s seamless for Snowflake’s customers.
Likewise, Snowflake doesn’t rely on subscriptions. Rather, it charges customers based on the data they store and the Snowflake Compute Credits they use. This transparent pricing policy really seems to resonate with its users.
The one issue with Snowflake is the company’s valuation. Don’t get me wrong, CrowdStrike trades at an immense premium, but has seen its sales remain robust. Snowflake’s revenue growth has slowed from the triple-digits three years ago to an estimated 22% in the current fiscal year. Snowflake is also valued at 115 times forward-year adjusted earnings, which is an even tougher pill to swallow for a company that’s seen its sales growth slow from the triple digits.
Though Snowflake looks to have a bright future, it could take some time before its operating performance grows into its current valuation.
Should you invest $1,000 in CrowdStrike right now?
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Source: finance.yahoo.com
The post Forget Nvidia: Billionaires Are Selling It and Buying These 2 Hypergrowth Artificial Intelligence (AI) Stocks Instead appeared first on HIPTHER Alerts.
The European Union (EU) has finalized the AI Act, a comprehensive regulatory framework designed to address the ethical, legal, and societal implications of artificial intelligence (AI). This landmark legislation has significant implications for employment law and compliance, affecting how organizations develop, deploy, and manage AI technologies. This article explores the key provisions of the EU AI Act and its impact on employment law and compliance.
Overview of the EU AI Act
The EU AI Act aims to ensure that AI technologies are developed and used in a manner that respects fundamental rights, promotes transparency, and mitigates risks. The legislation categorizes AI systems into different risk levels, imposing varying requirements based on the potential impact on individuals and society.
Key Provisions:
Risk-Based Approach: AI systems are categorized into four risk levels: unacceptable risk, high risk, limited risk, and minimal risk. High-risk AI systems are subject to stricter regulatory requirements.
Transparency and Accountability: Organizations must ensure transparency and accountability in the development and deployment of AI systems, including providing clear information about the functioning and decision-making processes.
Human Oversight: High-risk AI systems must incorporate human oversight to ensure that AI decisions can be reviewed and contested.
Data Governance: The Act imposes strict data governance requirements to ensure the quality, accuracy, and fairness of data used in AI systems.
Implications for Employment Law
The EU AI Act has significant implications for employment law, affecting how organizations use AI technologies in hiring, performance evaluation, and workplace monitoring.
Key Implications:
Fair Hiring Practices: AI systems used in hiring and recruitment must ensure fairness and non-discrimination, avoiding biases that could adversely impact candidates.
Performance Evaluation: AI-driven performance evaluation systems must be transparent and provide employees with the opportunity to contest decisions.
Workplace Monitoring: AI technologies used for workplace monitoring must respect employees’ privacy and comply with data protection regulations.
Compliance Requirements
Organizations must comply with the EU AI Act’s requirements to ensure the ethical and legal use of AI technologies. Compliance involves several key steps and considerations.
Compliance Steps:
Risk Assessment: Conducting a thorough risk assessment to categorize AI systems and determine the applicable regulatory requirements.
Transparency Measures: Implementing measures to ensure transparency in AI decision-making processes, including clear documentation and communication with affected individuals.
Human Oversight: Establishing mechanisms for human oversight and intervention in AI decision-making processes, particularly for high-risk AI systems.
Data Management: Ensuring robust data governance practices to maintain the quality, accuracy, and fairness of data used in AI systems.
Challenges in Compliance
Complying with the EU AI Act presents several challenges for organizations, requiring careful planning and execution.
Key Challenges:
Complexity: The complexity of the regulatory requirements can be challenging to navigate, particularly for organizations with multiple AI systems.
Data Management: Ensuring data quality and fairness requires robust data management practices and continuous monitoring.
Resource Allocation: Implementing compliance measures can be resource-intensive, requiring investment in technology, personnel, and training.
The Role of HR and Compliance Teams
Human resources (HR) and compliance teams play a critical role in ensuring that organizations comply with the EU AI Act and address its implications for employment law.
Key Responsibilities:
Policy Development: Developing and implementing policies that align with the EU AI Act’s requirements and promote ethical AI use.
Training and Education: Providing training and education for employees on the ethical and legal implications of AI technologies.
Monitoring and Auditing: Continuously monitoring and auditing AI systems to ensure compliance and address any issues that arise.
Future Prospects
The EU AI Act represents a significant step towards regulating AI technologies and ensuring their ethical and legal use. As organizations adapt to the new regulatory landscape, the focus will be on developing AI systems that are transparent, fair, and accountable.
Future Trends:
Innovation in Compliance: The development of innovative compliance solutions, such as AI-driven compliance tools, will help organizations navigate the regulatory landscape.
Global Impact: The EU AI Act is expected to influence AI regulation globally, setting a benchmark for other jurisdictions to follow.
Continuous Improvement: Organizations will continue to improve their AI systems and compliance practices, fostering a culture of ethical AI use.
Conclusion
The finalization of the EU AI Act has significant implications for employment law and compliance, requiring organizations to ensure the ethical and legal use of AI technologies. By adhering to the Act’s provisions and implementing robust compliance measures, organizations can navigate the complex regulatory landscape and promote transparency, fairness, and accountability in their AI systems. As the AI regulatory landscape continues to evolve, organizations must remain vigilant and proactive in addressing the ethical and legal challenges associated with AI.
Source of the news: SHRM
The post The EU AI Act Finalized: Implications for Employment Law and Compliance appeared first on HIPTHER Alerts.
The medical technology (Medtech) industry is at the forefront of healthcare innovation, developing cutting-edge solutions that improve patient outcomes and streamline healthcare delivery. However, compliance remains a critical concern, with regulatory requirements often viewed as a barrier to innovation. This article explores how compliance, rather than stifling innovation, can drive it by fostering a culture of quality, safety, and continuous improvement in the Medtech industry.
The Compliance Challenge in Medtech
The Medtech industry is subject to stringent regulatory requirements to ensure the safety and efficacy of medical devices. Compliance with these regulations is essential but can be resource-intensive and complex.
Key Compliance Requirements:
FDA Regulations: In the United States, the Food and Drug Administration (FDA) regulates medical devices, requiring rigorous testing and documentation to ensure safety and effectiveness.
EU MDR: The European Union’s Medical Device Regulation (EU MDR) sets stringent requirements for the marketing and distribution of medical devices in the EU.
ISO Standards: International standards, such as ISO 13485, provide a framework for quality management systems in the Medtech industry.
Compliance as a Driver of Innovation
While compliance is often seen as a barrier to innovation, it can also drive innovation by promoting a culture of quality and continuous improvement.
How Compliance Drives Innovation:
Quality Assurance: Compliance with regulatory requirements ensures that medical devices meet high standards of quality and safety, fostering trust and confidence among healthcare providers and patients.
Risk Management: Effective compliance programs help identify and mitigate risks, reducing the likelihood of product recalls and adverse events.
Continuous Improvement: Regulatory requirements encourage Medtech companies to continuously improve their processes and products, leading to innovative solutions that address unmet medical needs.
Market Access: Compliance with global regulatory standards enables Medtech companies to access international markets, expanding their reach and driving growth.
Balancing Compliance and Innovation
Medtech companies must strike a balance between compliance and innovation, ensuring that regulatory requirements do not stifle creativity and progress.
Strategies for Balancing Compliance and Innovation:
Integrated Compliance Programs: Developing integrated compliance programs that align with the company’s innovation goals and support a culture of quality and safety.
Collaborative Approach: Collaborating with regulatory agencies, industry partners, and stakeholders to develop innovative solutions that meet regulatory requirements.
Leveraging Technology: Utilizing advanced technologies, such as artificial intelligence (AI) and machine learning, to streamline compliance processes and enhance product development.
Continuous Training: Providing continuous training and education for employees to ensure they understand and adhere to regulatory requirements while fostering a culture of innovation.
Case Studies of Compliance-Driven Innovation
Several Medtech companies have successfully leveraged compliance as a driver of innovation, demonstrating that regulatory requirements can enhance, rather than hinder, progress.
Case Study Examples:
Innovative Product Development: A Medtech company developed a new medical device that met stringent regulatory requirements, resulting in a product that was safer and more effective than existing solutions.
Streamlined Approval Process: By developing a robust compliance program, a Medtech company streamlined the regulatory approval process, bringing their innovative product to market faster.
Global Market Access: Compliance with international standards enabled a Medtech company to expand into global markets, driving growth and innovation.
The Role of Regulatory Agencies
Regulatory agencies play a crucial role in fostering a compliance-driven culture of innovation in the Medtech industry.
Regulatory Agency Initiatives:
Innovation Pathways: Developing innovation pathways and expedited approval processes for breakthrough medical devices that address unmet medical needs.
Collaborative Partnerships: Forming collaborative partnerships with industry stakeholders to develop regulatory frameworks that support innovation.
Guidance and Support: Providing guidance and support to Medtech companies to help them navigate the regulatory landscape and develop compliant, innovative solutions.
Conclusion
Compliance in the Medtech industry is not a barrier to innovation but a driver of quality, safety, and continuous improvement. By fostering a culture of compliance and leveraging regulatory requirements as a catalyst for innovation, Medtech companies can develop cutting-edge solutions that improve patient outcomes and advance healthcare delivery. As the industry continues to evolve, balancing compliance and innovation will be essential for driving progress and ensuring the safety and efficacy of medical devices.
Source of the news: STAT News
The post Medtech Compliance: Not Regulation, but Innovation appeared first on HIPTHER Alerts.
Artificial intelligence (AI) is rapidly transforming the banking industry, providing innovative solutions to enhance operational efficiency, customer experience, and regulatory compliance. This article examines how AI can help banks navigate the complex regulatory compliance landscape, highlighting the benefits, challenges, and potential applications of AI in compliance.
The Regulatory Compliance Challenge
Banks operate in a highly regulated environment, with stringent requirements to ensure the integrity and stability of the financial system. Compliance with regulations such as anti-money laundering (AML), counter-terrorist financing (CTF), and data protection is crucial but can be resource-intensive and complex.
Key Compliance Requirements:
AML and CTF: Banks must monitor transactions to detect and prevent money laundering and terrorist financing activities.
Data Protection: Ensuring the privacy and security of customer data is paramount, particularly in light of regulations such as the General Data Protection Regulation (GDPR).
Reporting: Banks are required to submit detailed reports to regulators, demonstrating compliance with various regulatory requirements.
AI Applications in Regulatory Compliance
AI technologies offer a range of applications that can help banks streamline compliance processes, improve accuracy, and reduce costs.
Key AI Applications:
Transaction Monitoring: AI algorithms can analyze transaction data in real-time to identify suspicious activities and flag potential AML and CTF violations.
Customer Due Diligence: AI can automate the process of customer due diligence (CDD), verifying customer identities, and assessing risk profiles.
Regulatory Reporting: AI-powered tools can automate the collection, analysis, and submission of regulatory reports, ensuring timely and accurate compliance.
Risk Management: AI can analyze large datasets to identify and assess risks, enabling proactive risk management and mitigation.
Benefits of AI in Compliance
The integration of AI in regulatory compliance offers several benefits for banks, helping them navigate the complex regulatory landscape more effectively.
Key Benefits:
Efficiency: AI-driven automation reduces the time and effort required for compliance tasks, allowing banks to allocate resources more efficiently.
Accuracy: AI algorithms can process and analyze data with high precision, minimizing the risk of human error and ensuring accurate compliance.
Cost Savings: By automating compliance processes, AI can significantly reduce operational costs associated with regulatory compliance.
Scalability: AI solutions can scale to handle large volumes of data and transactions, making them suitable for banks of all sizes.
Challenges in Implementing AI for Compliance
Despite the benefits, implementing AI-driven compliance solutions also presents several challenges that banks must address.
Key Challenges:
Data Quality: The effectiveness of AI in compliance depends on the quality and completeness of the data. Banks must ensure that their data is accurate and up-to-date.
Regulatory Uncertainty: The regulatory landscape for AI is still evolving, and banks must stay abreast of new regulations and guidelines to ensure compliance.
Integration: Integrating AI solutions with existing systems and processes can be complex and requires careful planning and execution.
Ethical Considerations: Banks must consider the ethical implications of using AI, including issues related to transparency, fairness, and accountability.
Future Prospects of AI in Compliance
The future of AI-driven compliance in banking looks promising, with ongoing advancements in technology and increasing regulatory acceptance. As AI continues to evolve, it is expected to play an even more significant role in enhancing regulatory compliance and risk management.
Future Trends:
Advanced Analytics: The use of advanced analytics and machine learning algorithms will enable more sophisticated risk detection and management.
RegTech Solutions: Regulatory technology (RegTech) solutions that leverage AI will become more prevalent, providing banks with innovative tools to streamline compliance.
Collaboration with Regulators: Increased collaboration between banks and regulators will drive the development of AI standards and best practices for compliance.
Personalized Compliance: AI will enable personalized compliance solutions tailored to the specific needs and risk profiles of individual banks.
Conclusion
AI has the potential to revolutionize regulatory compliance in banking, offering significant benefits in terms of efficiency, accuracy, and scalability. While there are challenges to overcome, the future prospects of AI-driven compliance are bright, with ongoing advancements and increased regulatory acceptance paving the way for more innovative and effective solutions. As banks continue to embrace AI, they will be better equipped to navigate the complex regulatory landscape and ensure compliance in the digital age.
Source of the news: BizTech Magazine
The post Can AI Help Banks Navigate Regulatory Compliance? appeared first on HIPTHER Alerts.
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