Brand Stories
It’s Time for Humanity’s Best Exam for AI
Better benchmarks can unlock the social benefits of AI technology.
The rhythm of artificial intelligence (AI) development has become unsettlingly familiar. A new model is unveiled, and with it comes a predictable flurry of media attention. One cluster of articles dissects its intricate training data and architecture; another marvels, often breathlessly, at its newfound capabilities; and a third, almost inevitably, scrutinizes its performance on a battery of standardized tests. These benchmarks have become our primary yardsticks for AI progress. Yet, they predominantly paint a picture skewed toward raw technical prowess and potential peril, leaving the public with a pervasive feeling that each impressive step forward for AI might translate into two regrettable steps back for the rest of us.
Many of these evaluations concentrate on the technical capacity of the model or its computational horsepower. Others, with growing urgency, assess the likelihood of misuse—could this advanced AI empower rogue actors to design a bioweapon or destabilize critical infrastructure through sophisticated cyberattacks? A significant portion of evaluations also measures AI against human performance in specific job tasks, fueling widespread anxieties about automation and diminished human agency. The reporting on these tests, frequently framed by alarming headlines, understandably casts AI advancements more as a societal regression than a leap forward. The very branding of prominent benchmarks, such as the ominously titled Humanity’s Last Exam, amplifies these negative connotations. That benchmark and others like it tend to measure a model’s capacity to complete bespoke tests, aid bad actors engaging in harmful conduct, or some combination of the two. It is difficult, if not impossible, to read coverage of such an assessment and come away with a hopeful, or even neutral, view of AI’s trajectory.
This is not to argue that assessing risks or understanding the deep mechanics of AI is unimportant. Vigilance and technical scrutiny are crucial components of responsible development. The current benchmarking landscape, however, is dangerously imbalanced. Those of us who recognize AI’s immense transformative potential to address some of the world’s most intractable problems—including revolutionizing medical diagnostics, accelerating climate solutions, and personalizing education for every child—currently lack a prominent, public-facing benchmark designed to track, celebrate, and encourage these positive developments.
It is time we introduce “Humanity’s Best Exam”—a benchmark that strives to capture a model’s capacity to address public policy problems and otherwise serve the general welfare.
Imagine a new form of evaluation that challenges AI systems not with abstract logic puzzles but with tangible goals vital to human flourishing. Consider a benchmark that tasks AI models with identifying early-stage diabetic retinopathy from retinal scans with over 95 percent accuracy, a leap that could surpass current screening efficacy and save millions from preventable blindness. Picture a test that spurs the design of three novel antibiotic compounds that are effective against stubborn, drug-resistant bacteria within a single year. In the realm of climate science, Humanity’s Best Exam might push AI to develop a groundbreaking, cost-effective catalyst for the direct air capture of carbon dioxide, improving efficiency by a significant margin—say, 20 percent—over existing technologies. Or it could encourage the creation of predictive models for localized flash floods that offer vulnerable regions a critical six-hour lead time with 90 percent accuracy. Or, in education, the challenge could be to generate personalized six-month learning plans for diverse student profiles in foundational STEM subjects, demonstrably elevating learning outcomes by an average of two grade levels.
The creation and widespread adoption of Humanity’s Best Exam would serve several critical, society-shaping purposes.
First, it would powerfully harness the intense competitive spirit of AI laboratories for the global good. AI developers are profoundly motivated by benchmark performance—the race to the top of the leaderboards is fierce. Channeling this potent drive toward solving clearly defined societal problems could positively redirect research priorities and resource allocation within these influential organizations.
Second, such a benchmark would be instrumental in reshaping the public discourse surrounding artificial intelligence. The narrative around any powerful new technology is inevitably shaped by the information that is most readily available and most prominently featured. If the most visible AI assessments continue to highlight dangers and disruptions, public perception will remain tinged with fear and skepticism. Humanity’s Best Exam would provide a steady stream of positive, concrete examples of AI’s potential, offering a more balanced and hopeful counter-narrative. This perspective is essential for fostering a more informed and constructive public conversation, which is, in turn, vital for democratic oversight of this transformative technology.
Finally, a benchmark focused on positive societal impact would provide invaluable guidance for policymakers, investors, and researchers. As a law professor whose research centers on accelerating AI innovation through thoughtful legal and policy reforms, I see a pressing need for clearer signals to guide governance away from reactive, fear-driven legislation and toward proactive, enabling frameworks. Humanity’s Best Exam would illuminate areas where AI is poised to deliver significant societal returns, helping policymakers to direct strategic funding more effectively and to develop supportive, rather than stifling, regulatory environments. Investors would gain a clearer view of emerging opportunities where AI can create substantial financial and social value. Researchers across numerous disciplines could more easily identify how cutting-edge AI capabilities can be leveraged within their fields, potentially sparking new collaborations and accelerating vital research.
But who would build and oversee such an ambitious undertaking, and how could we navigate the inherent challenges? The establishment of Humanity’s Best Exam would necessitate a dedicated, independent, and broadly representative multi-stakeholder governing consortium. This body should ideally include experts from leading academic institutions, established nonprofits with proven experience in managing “grand challenges”—akin to the XPrize Foundation model that involves hosting competitions to achieve societally beneficial breakthroughs—relevant international organizations, domain specialists from fields such as public health, environmental science, and education, as well as ethicists and, critically, representatives from civil society organizations to ensure public accountability. Funding could be drawn from a diverse portfolio, including major philanthropic sources, government grants earmarked for scientific and societal advancement, and perhaps even a coalition of AI laboratories and technology firms committed to socially beneficial AI development.
To address the valid concern that defining “societal benefit” can be subjective, a primary task for this consortium would be to establish a transparent and evolving framework for identifying and prioritizing challenge areas, perhaps drawing inspiration from established global agendas such as the United Nation’s Sustainable Development Goals. The specific tasks within the benchmark would need to be rigorously defined, objectively measurable, and, crucially, regularly updated by diverse expert panels. This dynamism is key to preventing the benchmark from becoming stale, to avoiding the pitfalls of “teaching to the test” in a way that stifles genuine innovation, and to ensuring continued relevance as AI capabilities and societal needs evolve. Although no benchmark can ever be entirely immune to attempts at superficial optimization, focusing on complex, real-world problems with multifaceted success criteria makes simplistic gaming far more difficult than it is on narrower, purely technical tests. Furthermore, a portion of the assessment could incorporate qualitative reviews by expert panels, evaluating the robustness, safety, ethical considerations, and real-world applicability of the proposed AI tools.
The current, almost myopic focus on AI’s potential downsides, although born of a necessary caution, is inadvertently creating an innovation ecosystem shrouded in anxiety. We are meticulously documenting every conceivable way AI could go wrong, while failing to champion, encourage, and measure systematically its profound potential to go spectacularly right.
It is time to correct this imbalance. A crucial first step would be for leading philanthropic organizations, forward-thinking academic consortia, and ethically minded AI developers to convene a foundational summit. The purpose of such a gathering would be to begin outlining the charter, initial problem sets, and robust governance structure for Humanity’s Best Exam. This is far more than a mere intellectual exercise; it is a necessary reorientation of our collective focus and a deliberate effort to harness the awesome power of artificial intelligence for the betterment of all. Let us not only brace for AI’s potential last exam but actively architect its very best.
Key Points
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The chip industry is booming thanks to AI.
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Advanced Micro Devices is seeing margins and earnings soar as its data center business expands.
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Broadcom is meeting insatiable demand for custom AI chips and networking solutions for advanced AI workloads.
Artificial intelligence (AI) is impacting every sector of the economy, so there are several ways investors can profit from this opportunity. But recent earnings results show that top semiconductor companies are still well positioned to deliver outstanding returns for long-term investors.
The AI chip market is expected to grow at an annualized rate of 24% through 2029 to reach $311 billion, according to MarketsandMarkets. If you have $3,000 you’re looking to invest right now, here are two chip stocks to consider buying and holding for the long term.
Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Learn More »
Image source: Getty Images.
1. Advanced Micro Devices
Advanced Micro Devices(NASDAQ: AMD) has become a widely used brand of chips in the consumer PC market. Its Ryzen processors have taken significant market share from Intel. But it’s also one of only two suppliers, along with Nvidia, of general-purpose graphics processing units (GPUs) that are used for AI workloads.
While Nvidia has a commanding lead in GPUs, it’s not going to control 100% of the market. This leaves a substantial opportunity for the runner-up in this market to do well. AMD’s data center business is booming, with segment revenue up 57% year over year in the first quarter.
AMD is meeting demand for cost-effective alternatives in the chip market. Oracle is experiencing tremendous growth in its cloud infrastructure business right now, and it’s a key partner for AMD. Oracle’s cloud infrastructure will offer up to 131,072 AMD Instinct MI355X GPUs for AI. AMD has already announced the MI400 series for launch next year, which will enable even better performance for AI training and inferencing.
As data center sales make up a larger mix of AMD’s total revenue, it is pushing margins up. Higher margins drove a 55% year-over-year increase in adjusted earnings last quarter. Given the long-term opportunity in the AI chip market, which AMD estimates at $500 billion, investors are undervaluing AMD’s future earnings.
The stock is trading at a forward price-to-earnings (P/E) multiple of 38 on 2025 earnings estimates. But this multiple drops to 25 on 2026 estimates. As AMD continues to expand margins from growth in its data center business, the stock could offer significant upside over the next few years and beyond.
2. Broadcom
Beyond the surging demand for general-purpose chips that AMD supplies, there is growing demand for chips designed for specialized tasks. Broadcom(NASDAQ: AVGO) is one of the best stocks to profit from the demand for custom chip solutions.
Broadcom has been a top-performing semiconductor company for years, supplying components for many markets, including Apple‘s iPhone. But demand for its application-specific integrated circuits (ASICs) for AI is off the charts.
The company’s AI chip revenue grew 46% year over year in the most recent quarter. As demand for custom ASICs grows, it also fuels demand for networking products that can handle faster data transfer, which is needed for next-level AI performance.
Broadcom’s new Tomahawk 6 Ethernet switch has enough data capacity to support 100,000 AI chips working together to train the next-generation AI models. The company’s networking business posted revenue growth of 170% year over year last quarter, representing 40% of its AI-related revenue.
However, management sees the demand for its custom AI chips outpacing sales of its networking products over time. It’s a huge opportunity, as evidenced by Broadcom’s momentum. Management expects its AI growth to remain steady through fiscal 2026, which could support new highs for the stock.
Broadcom earns very high margins, so the favorable demand outlook points to robust earnings over the next year. The stock trades at 41 times this year’s consensus earnings estimate, but that multiple drops to 33 on next year’s estimate. These are not cheap valuation multiples, but the investment in AI technology is pointing to substantial growth in the coming years for leading chipmakers, and that should support excellent returns for investors.
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The market has returned to its highs, along with many top artificial intelligence (AI) names. However, another market dip could always be around the corner.
Let’s look at three top AI stocks that have made strong runs that would be good buys on a pullback.
Image source: Getty Images.
1. Palantir
With a high valuation but attractive growth opportunities, Palantir Technologies (PLTR -0.34%) is a stock that would be attractive on a dip. The company has emerged as one of the market’s most compelling AI growth stories, and its momentum has been gaining speed.
In the first quarter, Palantir posted its seventh consecutive period of accelerating growth, with revenue up 39%. The rise is being led by its U.S. commercial segments, which saw sales jump 71% and the value of future deals soar 127%.
While there is a lot of talk about which company is building the best AI model, Palantir is focused on something far more practical: making AI useful. Its Artificial Intelligence Platform (AIP) uses AI models to help solve real-world problems.
AIP does this by gathering data and then connecting it to physical assets and operational workflows, allowing companies to make AI more useful. As a result, the platform is being used for a growing list of purposes, including hospitals monitoring for sepsis, insurers using it in their underwriting, and energy companies optimizing their pipeline infrastructure.
The company’s largest customer is the U.S. government, which is starting to embrace AI to become more efficient. Last quarter, Palantir’s government revenue climbed 45%.
The company also recently landed a major deal with NATO, expanding into international defense just as Europe ramps up military spending. That gives it three potential growth engines: domestic commercial enterprises, the U.S. government, and now the international public sector.
Yes, the stock is expensive by traditional metrics, but Palantir looks like it’s laying the groundwork to become one of the next megacaps. As such, any pullback could be a great buying opportunity.
2. Nvidia
Nvidia (NVDA -0.42%) has once again been helping lead the market higher. The company recently got good news when the Trump administration said the U.S. would ease chip export controls, allowing the company to resume selling its H20 chips to China. This will add billions in revenue.
Nvidia remains the undisputed champion of AI infrastructure, with its graphics processing units (GPUs) the backbone of this build-out due to their fast processing speeds. And the company has sped up its development cycle to ensure it remains on top.
Over the past two years, data center revenue has exploded from $4.3 billion to more than $39 billion — incredible growth for a company the size of Nvidia. It held a 92% share in the GPU market in the first quarter.
Its chips drive sales, but its secret weapon is its CUDA software. The company created the free platform in 2006 as a way to expand the use of GPUs beyond their original purpose of speeding up graphics in video games.
While it was slow to play out in other end markets, Nvidia smartly pushed CUDA into academia and research labs, where early AI research was being done. That led developers to build directly on CUDA, leading to a growing collection of tools and libraries designed to maximize GPU performance for AI workloads.
If shares of Nvidia dip, be ready to pounce. Data center spending continues to ramp up, and the company has a big opportunity in the automotive market, too, as autonomous and smart vehicles start to become more prevalent.
3. Microsoft
Another company that has seen its stock run up in price is Microsoft (MSFT -0.32%). It dominates the enterprise software space with its Microsoft 365 suite of worker productivity products and has one of the leading cloud computing companies in Azure.
The cloud remains the company’s fastest-growing business, with the unit producing revenue growth of 30% or more each of the past seven quarters. Azure revenue jumped 33% last quarter (35% in constant currency), with nearly half of that coming from AI services. Growth could have been even higher, but Microsoft has been hitting capacity constraints.
As such, it plans to ramp up capital expenditures (capex) in fiscal 2026 with a focus on adding GPUs and servers. It said those assets are more directly tied to AI revenue than buying the buildings that house them. That’s a smart move that should support continued cloud computing momentum.
Microsoft’s $10 billion investment in OpenAI gave it an early AI lead, especially with Azure initially being granted exclusive access to its leading large language models (LLMs). Companies continue to be attracted to OpenAI’s popular AI models, and Azure gives its customers direct access to them.
It has also embedded OpenAI’s models throughout its ecosystem to run its Copilot, which is gaining popularity with businesses. At $30 per enterprise user per month, it offers a lot of strong upside.
That said, the OpenAI partnership is getting complicated. The exclusivity deal is over, and the two sides are reportedly negotiating new terms as the AI provider looks to restructure. Still, Microsoft remains entitled to 49% of OpenAI Global’s profits up to a tenfold return on its investment — potentially a huge payday.
Microsoft remains in a strong long-term position. The stock’s recent run-up makes it an attractive candidate to buy on any pullback.
Brand Stories
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