The financial world is undergoing a seismic shift, driven by the rapid integration of artificial intelligence (AI) into investment strategies. From stock selection to portfolio optimization, risk management to predictive analytics, AI is transforming how investors—both individual and institutional—approach wealth creation. This revolution is not just about automation; it’s about leveraging unprecedented computational power to uncover opportunities, mitigate risks, and deliver personalized investment solutions at scale. In this article, we explore how AI is reshaping investment portfolios, highlight key companies providing exposure to this megatrend, and discuss the opportunities and risks for investors in 2025 and beyond.
The AI Revolution in Investing: A New Era of Data-Driven Decisions
Artificial intelligence, encompassing machine learning, natural language processing, and predictive analytics, is redefining the investment landscape. Unlike traditional strategies that rely heavily on human judgment, AI processes vast datasets—market trends, financial statements, news sentiment, and even social media activity—in real time to identify patterns and make informed decisions. This capability allows investors to act faster, more accurately, and with less emotional bias.
Key applications of AI in investing include:
Stock Selection: AI-powered algorithms analyze thousands of data points to identify undervalued stocks or predict price movements.
Portfolio Optimization: Machine learning models fine-tune asset allocations to maximize returns for a given risk level, often using modern portfolio theory’s efficient frontier.
Risk Management: AI systems monitor market conditions, detect potential downturns, and execute risk-mitigation strategies like stop-loss orders or portfolio rebalancing.
Predictive Analytics: By analyzing historical and real-time data, AI forecasts market trends, economic cycles, and company performance.
Robo-Advisors: Platforms like Wealthfront and Betterment use AI to create personalized portfolios based on investor goals, risk tolerance, and time horizons.
These advancements are democratizing access to sophisticated investment strategies, making them available to retail investors through user-friendly apps and platforms. However, the true power of AI lies in its ability to scale these capabilities across global markets, offering unparalleled efficiency and insight.
Key Companies Driving the AI Investment Revolution
Investors seeking exposure to AI can choose from a range of companies at the forefront of this technological wave. These include AI-native firms, legacy tech giants integrating AI into their operations, and infrastructure providers enabling AI development. Below, we highlight key players, their exchange and ticker symbols, and their recent performance as of July 2025.
NVIDIA is the undisputed leader in AI hardware, particularly graphics processing units (GPUs) that power advanced AI applications. Its CUDA platform and Blackwell GPUs are critical for training and deploying large language models (LLMs) and generative AI systems. NVIDIA’s market cap has surpassed $3 trillion, driven by soaring demand from cloud providers and enterprises.
Recent Results: In Q3 2025, NVIDIA reported revenues of $35.1 billion, up 94% year-over-year, with AI-related sales accounting for the lion’s share. Analysts project 38% annual earnings growth over the next three years.
Why Invest? NVIDIA’s dominance in the AI chip market, coupled with its vertical integration across hardware and software, positions it as a cornerstone of the AI ecosystem. However, risks include reliance on a few large customers (e.g., Microsoft) and potential competition from rivals like AMD.
Microsoft has embedded AI across its product portfolio, from Azure cloud services to Office 365’s Copilot and Edge browser. Its $13 billion investment in OpenAI, the creator of ChatGPT, underscores its commitment to leading the AI race. Azure OpenAI serves over 65% of Fortune 500 companies, making Microsoft a key enabler of enterprise AI adoption.
Recent Results: In its latest quarter, Microsoft reported 16% revenue growth, with Azure’s AI-driven cloud services growing 50% year-over-year. The company is diversifying its AI offerings by integrating third-party models like DeepSeek’s R1 into Azure.
Why Invest? Microsoft’s diversified revenue streams and strategic AI partnerships provide stability and growth potential. Its role as a cloud and software giant makes it a less volatile AI play compared to pure-play chipmakers.
Alphabet, Google’s parent company, leverages AI across its ecosystem, from search algorithms to Waymo’s autonomous vehicles and Google Cloud’s AI tools. Its Gemini 2.5 model, launched in December 2023, is widely regarded as a leading LLM, competing with ChatGPT. Alphabet’s DeepMind acquisition in 2014 has bolstered its AI research capabilities.
Recent Results: Alphabet’s Q2 2025 earnings showed 14% revenue growth, driven by AI-enhanced ad pricing and Google Cloud’s 35% growth. Gemini 2.5 has strengthened Alphabet’s position in generative AI.
Why Invest? Alphabet’s vast data resources and AI expertise make it a long-term winner in AI applications. However, regulatory scrutiny over data privacy and antitrust concerns could pose challenges.
Amazon uses AI to optimize its e-commerce operations, recommendation engines, and AWS cloud services. AWS is a leading provider of AI infrastructure, offering tools like SageMaker for building custom AI models. Amazon’s Alexa and autonomous delivery drones further demonstrate its AI prowess.
Recent Results: Amazon’s Q1 2025 results showed 13% revenue growth, with AWS growing 17% due to AI workload demand. The company is investing heavily in AI-driven logistics and cloud computing.
Why Invest? Amazon’s scale and diversified business model offer a balanced way to gain AI exposure. Its focus on customer-facing AI applications aligns with 2025’s shift toward inference-driven growth.
Broadcom designs application-specific integrated circuits (ASICs) critical for AI data centers. Its blue-chip clients include Amazon, Alphabet, Microsoft, and IBM, positioning it as a key supplier in the AI infrastructure buildout. Broadcom’s stock doubled in 2024, reflecting its growing AI relevance.
Recent Results: In Q4 2024, Broadcom reported $14.05 billion in revenue, up 51% year-over-year, driven by AI-related chip demand. Analysts expect continued growth as data center investments accelerate.
Why Invest? Broadcom’s niche in AI-specific chips and strong client relationships make it a compelling pick. However, its high valuation requires careful consideration.
Arista provides high-performance cloud networking solutions, including Gigabit Ethernet switches and routers used in AI data centers. Its products support the massive data throughput required for AI workloads, serving clients like Microsoft and Meta.
Recent Results: Arista’s Q1 2025 results showed 34% revenue growth, driven by AI-driven data center demand. Its focus on next-generation networking positions it for sustained growth.
Why Invest? Arista’s specialized role in AI infrastructure offers high growth potential. Its smaller market cap compared to tech giants makes it a riskier but potentially rewarding investment.
Palantir’s AI-driven data analytics platforms, Gotham and Foundry, serve government and enterprise clients. Its AIP (Artificial Intelligence Platform) has gained traction for automating complex workflows, making Palantir a leader in applied AI.
Recent Results: Palantir’s Q1 2025 revenue grew 27%, with commercial AI solutions driving growth. Its high valuation reflects investor enthusiasm but also introduces volatility.
Why Invest? Palantir’s focus on AI applications in defense and enterprise sectors offers unique exposure. However, its profitability challenges and dependence on government contracts warrant caution.
AMD competes with NVIDIA in the AI chip market, particularly with its MI300 accelerator. While it has struggled to gain market share, AMD’s GPUs are used in data centers and gaming, providing diversified AI exposure.
Recent Results: AMD’s Q1 2025 revenue grew 9%, with data center GPUs showing promise. However, its AI market share remains small compared to NVIDIA’s dominance.
Why Invest? AMD offers a lower-cost alternative to NVIDIA with potential upside if it gains AI market traction. Its slower growth trajectory makes it a riskier bet.
AI-Powered ETFs: Diversified Exposure to the AI Megatrend
For investors wary of picking individual stocks, AI-focused exchange-traded funds (ETFs) offer diversified exposure. These funds invest in a basket of AI-related companies, reducing single-stock risk. Below are top AI ETFs as of mid-2025:
Global X Artificial Intelligence & Technology ETF (NASDAQ: AIQ): With 86 holdings, including NVIDIA, Microsoft, and Amazon, AIQ is the largest AI ETF, managing over $2 billion in assets. It has returned 18% year-to-date in 2025.
iShares Future AI & Tech ETF (NYSE: ARTY): Formerly IRBO, ARTY holds 49 stocks, including AMD and Vertiv Holdings, with a focus on small-cap AI innovators. It offers 15% year-to-date returns.
Amplify AI Powered Equity ETF (NYSE: AIEQ): Powered by IBM’s Watson, AIEQ uses AI to select stocks dynamically. Despite underperforming the S&P 500, it provides unique AI-driven management with 12% year-to-date returns.
ETFs like these track indices such as the Indxx Global Robotics & Artificial Intelligence Thematic Index, offering exposure to both established giants and emerging players. However, investors should scrutinize expense ratios and holdings to ensure alignment with their goals.
The Benefits of AI in Portfolio Management
AI’s integration into investing offers tangible benefits, transforming how portfolios are constructed and managed:
Enhanced Efficiency: AI automates repetitive tasks like data analysis, freeing investment professionals to focus on strategy and client engagement. BlackRock, for instance, has replaced some human stock-pickers with AI-driven algorithms, citing improved performance.
Real-Time Insights: AI tools like Forecaster’s AI Agent provide 24/7 market analysis, tracking global trends and economic cycles to inform timely decisions.
Personalization: Robo-advisors use AI to tailor portfolios to individual risk profiles, making sophisticated strategies accessible to retail investors.
Uncovering Hidden Opportunities: AI analyzes alternative data sources, such as social media sentiment or supply chain logistics, to identify undervalued assets or emerging trends.
These advantages are driving adoption across the investment industry, with 93% of private equity firms expecting moderate to significant AI-driven value within three to five years.
Risks and Challenges of AI-Driven Investing
While AI offers immense potential, it’s not without risks. Investors must navigate these challenges to harness AI’s benefits effectively:
Overreliance on Algorithms: AI systems depend on historical data, which may not account for unprecedented events like geopolitical crises or market shocks. Human oversight remains critical.
High Valuations: AI stocks like NVIDIA and Palantir trade at premium multiples, raising concerns about a potential bubble. Forward P/E trends suggest some sectors may be oversaturated.
Regulatory Scrutiny: AI’s data-intensive nature invites regulatory oversight, particularly around privacy and ethical concerns. Country-specific regulations could impact growth.
Fraudulent Schemes: The SEC has warned of AI-related investment scams, where fraudsters exploit AI’s hype with promises of “guaranteed returns.” Investors must exercise due diligence.
Market Volatility: The AI sector’s rapid growth introduces volatility, as investor sentiment can shift quickly. Diversification through ETFs or legacy companies like Microsoft can mitigate this risk.
The Future of AI in Investing: Trends to Watch in 2025
As AI continues to evolve, several trends are shaping its role in investment portfolios:
Shift to Customer-Facing Applications: Investment focus is moving from foundational AI (e.g., chips and models) to inference-driven applications like AI-powered products and services. This shift favors companies like Amazon and Palantir.
Increased Focus on Profitability: Investors are prioritizing AI-native companies with strong annual recurring revenue (ARR) and mid-term profitability, balancing risk and reward.
Ethical AI Governance: Firms adopting transparent and fair AI practices will gain investor trust, especially as ethical concerns around bias and privacy grow.
Hybrid Human-AI Models: The most successful strategies will combine AI’s computational power with human expertise, as seen in BlackRock’s Thematic Robot tool.
Global AI Infrastructure Buildout: With projections of $1 trillion in AI-related capital expenditure over the next few years, companies like Broadcom and Arista will benefit from data center expansion.
How to Get Started with AI Investing
For investors eager to capitalize on the AI revolution, here are practical steps to build exposure:
Research Key Players: Focus on companies with proven AI track records, such as NVIDIA (NASDAQ: NVDA), Microsoft (NASDAQ: MSFT), and Alphabet (NASDAQ: GOOGL). Use stock screeners like Zacks to filter for AI-related metrics.
Consider ETFs: AI ETFs like Global X AIQ (NASDAQ: AIQ) offer diversified exposure with lower risk. Review holdings and expense ratios to align with your goals.
Use AI Tools: Platforms like Ainvest and Streetbeat provide AI-powered stock screeners and portfolio analysis, helping you identify opportunities.
Diversify: Limit AI exposure to 10% of your portfolio to manage risk, complementing it with broader market investments like S&P 500 index funds.
Stay Informed: Follow market trends through AI-driven platforms like Forecaster or trusted financial news sources. Monitor regulatory developments and earnings reports.
Conclusion: Embracing the AI-Powered Future
Artificial intelligence is not just revolutionizing investment portfolios—it’s redefining the very nature of wealth creation. By harnessing AI’s ability to process data, predict trends, and optimize strategies, investors can achieve greater precision and efficiency. Companies like NVIDIA (NASDAQ: NVDA), Microsoft (NASDAQ: MSFT), Alphabet (NASDAQ: GOOGL), and others are leading this charge, offering diverse ways to gain exposure. Meanwhile, AI-powered ETFs and tools make these opportunities accessible to all.
However, the AI revolution comes with caveats. High valuations, regulatory risks, and overreliance on algorithms demand careful navigation. By combining AI’s capabilities with human judgment, diversifying investments, and staying informed, investors can position themselves to thrive in this transformative era.
As Dr. Martinez aptly puts it, “AI is the fire of the Third Industrial Revolution. Those who learn to wield it will shape the future of finance.”
Disclaimer: This article is for informational purposes only and does not constitute investment advice. Always conduct thorough research and consult a financial advisor before making investment decisions.
A hacker has pulled off one of the most alarming AI-powered cyberattacks ever documented. According to Anthropic, the company behind Claude, a hacker used its artificial intelligence chatbot to research, hack, and extort at least 17 organizations. This marks the first public case where a leading AI system automated nearly every stage of a cybercrime campaign, an evolution that experts now call “vibe hacking.”
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Simulated ransom guidance created by Anthropic’s threat intelligence team for research and demonstration purposes.(Anthropic)
How a hacker used an AI chatbot to strike 17 targets
Anthropic’s investigation revealed how the attacker convinced Claude Code, a coding-focused AI agent, to identify vulnerable companies. Once inside, the hacker:
Built malware to steal sensitive files.
Extracted and organized stolen data to find high-value information.
Calculated ransom demands based on victims’ finances.
Generated tailored extortion notes and emails.
Targets included a defense contractor, a financial institution and multiple healthcare providers. The stolen data included Social Security numbers, financial records and government-regulated defense files. Ransom demands ranged from $75,000 to over $500,000.
Why AI cybercrime is more dangerous than ever
Cyber extortion is not new. But this case shows how AI transforms it. Instead of acting as an assistant, Claude became an active operator scanning networks, crafting malware and even analyzing stolen data. AI lowers the barrier to entry. In the past, such operations required years of training. Now, a single hacker with limited skills can launch attacks that once took a full criminal team. This is the frightening power of agentic AI systems.
A cybercriminal’s initial sales offering on the dark web seen in January 2025.(Anthropic)
How Anthropic is responding to AI abuse
Anthropic says it has banned the accounts linked to this campaign and developed new detection methods. Its threat intelligence team continues to investigate misuse cases and share findings with industry and government partners. The company admits, however, that determined actors can still bypass safeguards. And experts warn that these patterns are not unique to Claude; similar risks exist across all advanced AI models.
How to protect yourself from AI cyberattacks
Here’s how to defend against hackers now using AI tools to their advantage:
1. Use strong, unique passwords everywhere
Hackers who break into one account often attempt to use the same password across your other logins. This tactic becomes even more dangerous when AI is involved because a chatbot can quickly test stolen credentials across hundreds of sites. The best defense is to create long, unique passwords for every account you have. Treat your passwords like digital keys and never reuse the same one in more than one lock.
Next, see if your email has been exposed in past breaches. Our No. 1 password manager (see Cyberguy.com/Passwords) pick includes a built-in breach scanner that checks whether your email address or passwords have appeared in known leaks. If you discover a match, immediately change any reused passwords and secure those accounts with new, unique credentials.
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2. Protect your identity and use a data removal service
The hacker who abused Claude didn’t just steal files; they organized and analyzed them to find the most damaging details. That illustrates the value of your personal information in the wrong hands. The less data criminals can find about you online, the safer you are. Review your digital footprint, lock down privacy settings, and reduce what’s available on public databases and broker sites.
While no service can guarantee the complete removal of your data from the internet, a data removal service is really a smart choice. They aren’t cheap, and neither is your privacy. These services do all the work for you by actively monitoring and systematically erasing your personal information from hundreds of websites. It’s what gives me peace of mind and has proven to be the most effective way to erase your personal data from the internet. By limiting the information available, you reduce the risk of scammers cross-referencing data from breaches with information they might find on the dark web, making it harder for them to target you.
Check out my top picks for data removal services and get a free scan to find out if your personal information is already out on the web by visiting Cyberguy.com/Delete
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Illustration of a hacker at work.(Kurt “CyberGuy” Knutsson)
3. Turn on two-factor authentication (2FA)
Even if a hacker obtains your password, 2FA can stop them in their tracks. AI tools now help criminals generate highly realistic phishing attempts designed to trick you into handing over logins. By enabling 2FA, you add an extra layer of protection that they cannot easily bypass. Choose app-based codes or a physical key whenever possible, as these are more secure than text messages, which are easier for attackers to intercept.
4. Keep devices and software updated
AI-driven attacks often exploit the most basic weaknesses, such as outdated software. Once a hacker knows which companies or individuals are running old systems, they can use automated scripts to break in within minutes. Regular updates close those gaps before they can be targeted. Setting your devices and apps to update automatically removes one of the easiest entry points that criminals rely on.
5. Be suspicious of urgent messages
One of the most alarming details in the Anthropic report was how the hacker used AI to craft convincing extortion notes. The same tactics are being applied to phishing emails and texts sent to everyday users. If you receive a message demanding immediate action, such as clicking a link, transferring money or downloading a file, treat it with suspicion. Stop, check the source and verify before you act.
6. Use a strong antivirus software
The hacker in this case built custom malware with the help of AI. That means malicious software is getting smarter, faster and harder to detect. Strong antivirus software that constantly scans for suspicious activity provides a critical safety net. It can identify phishing emails and detect ransomware before it spreads, which is vital now that AI tools make these attacks more adaptive and persistent.
Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android & iOS devices at Cyberguy.com/LockUpYourTech
Over 40,000 Americans were previously exposed in a massive OnTrac security breach, leaking sensitive medical and financial records.(Jakub Porzycki/NurPhoto via Getty Images)
7. Stay private online with a VPN
AI isn’t only being used to break into companies; it’s also being used to analyze patterns of behavior and track individuals. A VPN encrypts your online activity, making it much harder for criminals to connect your browsing to your identity. By keeping your internet traffic private, you add another layer of protection for hackers trying to gather information they can later exploit.
For the best VPN software, see my expert review of the best VPNs for browsing the web privately on your Windows, Mac, Android & iOS devices at Cyberguy.com/VPN
AI isn’t just powering helpful tools; it’s also arming hackers. This case proves that cybercriminals can now automate attacks in ways once thought impossible. The good news is, you can take practical steps today to reduce your risk. By making smart moves, such as enabling two-factor authentication (2FA), updating devices, and using protective tools, you can stay one step ahead.
Do you think AI chatbots should be more tightly regulated to prevent abuse? Let us know by writing to us at Cyberguy.com/Contact
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Kurt “CyberGuy” Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on “FOX & Friends.” Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.
In a groundbreaking shift that’s reshaping medical research, universities across North America and Europe are increasingly bypassing traditional ethics reviews for studies involving AI-generated synthetic medical data. According to a recent report in Nature, representatives from four prominent medical research centers—including institutions in Canada, the United States, and Italy—have confirmed they’ve waived standard institutional review board (IRB) approvals for such projects. The rationale? Synthetic data, created by algorithms that mimic real patient records without containing traceable personal information, doesn’t pose the same privacy risks as actual human data. This move is accelerating fields like drug discovery and disease modeling, where access to vast datasets is crucial but often hampered by regulatory hurdles.
Proponents argue that this approach could unlock unprecedented innovation. For instance, AI systems can generate hypothetical patient profiles—complete with symptoms, genetic markers, and treatment outcomes—based on anonymized real-world patterns. Researchers at these centers told Nature that by eliminating the need for lengthy ethics approvals, which can delay projects by months, they’re speeding up trials for rare diseases and personalized medicine. A similar sentiment echoes in a WebProNews analysis, which highlights how synthetic data is being used to train machine-learning models for predicting cancer progression without ever touching sensitive health records.
The Ethical Tightrope: Balancing Speed and Scrutiny in AI-Driven Research This waiver trend isn’t without controversy, as critics warn it could erode foundational safeguards. Ethical guidelines from the World Health Organization, outlined in their 2024 guidance on AI in healthcare, emphasize the need for governance to address biases in large multi-modal models. If synthetic data inherits flaws from the original datasets—such as underrepresentation of minority groups—it might perpetuate inequities in medical AI, leading to skewed diagnostics or treatments. Posts on X (formerly Twitter) reflect growing public concern, with users debating privacy implications and calling for stricter oversight, often citing fears that “synthetic” doesn’t mean “safe” from algorithmic errors.
Moreover, a 2025 study in Frontiers in Medicine reviews a decade of global AI medical device regulations, noting that while synthetic data sidesteps patient consent issues, it raises questions about accountability. Who verifies the accuracy of AI-generated datasets? In one example from the Nature report, a Canadian university used synthetic data to simulate COVID-19 vaccine responses, bypassing IRB review and completing the study in weeks rather than months. Yet, as another Nature piece cautions, artificially generated data must be rigorously validated to avoid misleading results that could harm real-world applications.
Regulatory Gaps: Calls for Harmonized Standards Amid Rapid AI Adoption The pushback is intensifying, with experts advocating for updated frameworks. A 2024 article in Humanities and Social Sciences Communications identifies key challenges like health equity and international cooperation, urging harmonized regulations to prevent a patchwork of standards. In the U.S., the FDA has begun scrutinizing AI tools, but synthetic data often falls into a gray area, as noted in PMC’s 2021 overview of AI ethics in medicine. European regulators, influenced by GDPR, are more cautious, yet Italian centers are among those waiving reviews, per Nature.
Industry insiders see this as a double-edged sword: faster research could lead to breakthroughs, but without robust checks, trust in AI healthcare might falter. Recent X discussions amplify this, with tech influencers warning of “bias amplification” in synthetic datasets. As one researcher quoted in WebProNews put it, the shift demands “updated regulations to balance innovation with accountability.” Looking ahead, organizations like WHO are pushing for global guidelines, potentially mandating third-party audits for synthetic data projects.
Future Implications: Navigating Innovation and Risk in a Data-Driven Era Ultimately, this development signals a broader transformation in how AI intersects with medicine. By 2025, as per Frontiers’ analysis, AI integration in diagnostics is expected to surge, with synthetic data playing a pivotal role. However, ethical lapses could undermine public confidence, especially if biases lead to real harms. Universities must collaborate with regulators to ensure synthetic data’s promise doesn’t come at the cost of integrity, setting a precedent for responsible AI use worldwide.
AI is everywhere, it can be overwhelming, and lots of folks will be sick of hearing about it. But it’s also important to continue to recognize where AI can make a real difference, including in helping our understanding of the universe.
That’s exactly what’s been happening at Oxford University, one of the UK’s most respected academic centers. A new tool built by its researchers is enabling them to find “the needles in a cosmic haystack” while significantly reducing the workload on its scientists conducting the research.
Specifically what’s been presented is an AI-powered tool that is helping astronomers find supernovae by providing an efficient way to comb through hundreds of signals per day that would take up hours of manpower ordinarily to manually sift through.
Instead, this new approach using the power of AI reduces the human aspect of the workload by as much as 85%, while maintaining an outstanding accuracy record and freeing up scientists to better use their time, and their minds.
The Virtual Research Assistant is efficient and accurate and reduces the load on the astronomers who would ordinarily have processed the data manually. (Image credit: Getty Images | Javier Zayas Photography)
“The new tool, called the Virtual Research Assistant (VRA), is a collection of automated bots that mimics the human decision-making process by ranking alerts based on their likelihood of being real, extragalactic explosions. Unlike many AI-automated approaches that require vast training data and supercomputers, the VRA uses a leaner approach. Instead of data-hungry deep learning methods, the system uses smaller algorithms based on decision trees that looks for patterns in selected aspects of the data. This allows scientists to inject their expertise directly into the model and guide the algorithms to key features to look for.”
One of the key takeaways besides the obvious time saving aspect for the scientists using it is that the VRA wasn’t built like an LLM, using massive datasets and equally massive quantities of computing power and energy.
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Instead, it was possible to train using just 15,000 examples and a laptop to train the algorithms used in the VRA.
Unlike a traditional LLM, it was possible to train the VRA using nothing but a laptop. (Image credit: Windows Central | Zachary Boddy)
It continues to update its assessments of the signals as the same patch of sky is re-scanned, and as such only the most likely positive signals get passed to the astronomers for final verification.
In the first year of use, it processed over 30,000 alerts and missed less than 0.08% of real ones.
With a new survey starting in 2026 that will produce up to 10 million alerts per night, having an AI tool that can reduce workload for the humans by 85% certainly sounds like it arrived at the right time.
I won’t pretend to understand any of the science, but this is proof if ever it were needed of the benefits AI can provide. A human with the right expertise still has the final signoff, but properly trained AI can crunch significant quantities of data faster and make the end job for that human more efficient.
AI isn’t always about asking ChatGPT to help with a recipe or researching your homework. In the right hands, it can do phenomenal work to change the way we understand the universe around us.
