Researchers are increasingly using artificial intelligence technologies to help solve some of the biggest challenges facing the energy sector — including, ironically, the massive surge in electricity demand caused by large language models themselves. The current and expected rise in energy consumption from AI data centers is driving a wave of investment into advanced energy alternatives capable of delivering huge amounts of reliable electricity without major greenhouse gas emissions.

Among the technologies being viewed as a potential “silver bullet” is nuclear fusion, which has made major progress in laboratories in recent years, partly thanks to AI tools.

In this context, scientists at Ames National Laboratory in Ames, Iowa, are developing a specialized AI tool designed to model how different materials behave inside nuclear fusion systems, with the goal of improving research methods and making both the scientific process and fusion systems more efficient.

The tool, known as “DuctGPT,” was developed based on an earlier model from the National Institute of Standards and Technology called “AtomGPT.” The “Duct” version combines large language models with physics-based simulations to identify materials capable of withstanding the harsh environment inside a nuclear fusion reactor.

Nuclear fusion — the same process that powers the sun — relies on extremely high temperatures that most materials cannot tolerate. In addition to resisting temperatures reaching thousands, millions, or even hundreds of millions of degrees, these materials must also remain sufficiently ductile to allow practical manufacturing.

Finding the right material remains one of the biggest obstacles preventing commercial nuclear fusion, while also representing a massive opportunity for the scientific team capable of solving the challenge, potentially unlocking a near-unlimited source of clean energy. Identifying such materials requires exploring and modeling an enormous range of possible alloy combinations.

This type of project is particularly well suited to large language models. In a Financial Times report published last year titled “How AI Could Deliver More Energy Than It Consumes,” the newspaper noted that “discovering new materials, catalysts, or processes capable of producing energy more efficiently is exactly the type of ‘needle in a haystack’ problem where AI excels.”

The new tool is already showing highly promising results in fusion research. The team behind “DuctGPT” said the time required to discover new alloys for fusion experiments has been reduced from months of research work to just a few hours.

Scientist Prashant Singh from Ames Laboratory said: “Now when you ask the system to design a material for nuclear fusion with the critical properties required for reactors, it provides the appropriate elemental compositions along with their expected characteristics.”

Although “DuctGPT” is one of the newest and most promising applications of large language models in nuclear energy research, it is not the only one. Another tool called “Diag2Diag” is being used to help monitor and control plasma behavior in fusion experiments, specifically to prevent a phenomenon known as “Edge Localized Mode” or “ELM.”

This instability rapidly erodes the materials surrounding the plasma, creating major challenges in massive and expensive projects such as Europe’s ITER reactor and China’s EAST reactor.

In the United Kingdom, the British government is investing £45 million, or roughly $60 million, to build an AI-powered supercomputer at the UK Atomic Energy Authority campus in Oxfordshire.

The computer, called “Sunrise,” is expected to begin operations next month. According to a report published by Interesting Engineering in March, officials say the system will help scientists better understand the highly complex physics inside fusion reactors.

The report added that combining advanced computing with AI models could allow researchers to test ideas virtually before building extremely expensive experimental systems.

Together, these tools could dramatically accelerate nuclear fusion research at a time when the need for breakthroughs has become more urgent than ever. While investing in unproven technologies remains a high-risk bet, nuclear fusion now appears closer to reality than at any previous point, as scientific breakthroughs accelerate, competition intensifies, and major technology companies move aggressively into the sector.

The enormous and unprecedented energy demand created by artificial intelligence has become so large that the tools needed to address it may also need to be unprecedented — which helps explain why AI solutions themselves may ultimately become the only way to solve the problems AI created in the first place.

Wall Street indexes opened sharply lower on Friday after fears of rising inflation driven by the Middle East conflict pushed US Treasury yields higher, threatening to halt the AI-driven rally that has fueled markets in recent months.

The Dow Jones Industrial Average fell 133.2 points, or 0.27%, at the open to 49,930.26 points.

The S&P 500 also declined by 56.1 points, or 0.75%, to 7,445.11 at the start of trading.

Meanwhile, the Nasdaq Composite dropped 346.3 points, or 1.30%, to 26,288.923 as the opening bell rang.

The continued closure of the Strait of Hormuz has triggered a sharp rise in sulfur prices, causing major repercussions for Indonesia’s nickel sector. The disruption comes amid ongoing supply chain turmoil, heavily impacting a country that relies significantly on Gulf imports to support its nickel processing operations.

As Indonesia struggles to cope with sulfur supply shortages, political and regulatory changes are adding further pressure on the sector.

These developments are reshaping expectations for the global nickel market, with slowing domestic production leading analysts to forecast a shift from oversupply toward a market deficit by 2026.

As the crisis continues to evolve, nickel prices have risen, signaling that markets are adapting to tighter supplies and higher costs.

Investors have also begun positioning strategically in response to Indonesia’s ongoing policy moves and the geopolitical tensions affecting global sulfur supplies.

The latest Bitcoin price news showed heavy pressure on May 13, after investors pulled $635 million from Bitcoin exchange-traded funds (ETFs) in a single session, marking the largest outflow since January and pushing the cryptocurrency below the $80,000 level for the first time in six weeks.

It appears that the quiet holding phase has ended, with future returns now increasingly tied to how quickly investors reposition themselves. While retail investors continue to retreat, capital flows are still moving into a presale project that has raised more than $10 million during the same wave of fear.

Pepeto continues attracting funds from investment wallets that appear to have already chosen their next bet, as the project approaches a potential listing on Binance.

Bitcoin news shakes the ETF market

US spot Bitcoin ETFs recorded net outflows of $635 million on May 13, led by BlackRock’s IBIT fund, which alone saw withdrawals totaling $285 million, according to CoinDesk.

Based on Yahoo Finance data, total redemptions over the past five sessions reached around $1.26 billion.

Bitcoin fell to $79,300 after failing four consecutive times to break above the 200-day moving average near $82,000, while US consumer inflation reaching 3.8% erased hopes for interest rate cuts during 2026.

Although current Bitcoin news reflects signs of panic, every previous correction cycle in the crypto market eventually ended with a rally that rewarded wallets maintaining their positions.

Where Bitcoin and Pepeto stand amid shifting capital flows

Pepeto project

This week’s Bitcoin news triggered $635 million in ETF outflows, yet the broader crypto market fundamentals continue improving, while one presale project successfully attracted capital freed from those withdrawals.

Pepeto has raised more than $10 million from investment wallets that, according to the project, recognized the signals before the broader market.

The project claims that one of the co-founders behind the original Pepe coin, which previously reached an $11 billion market capitalization without offering real products, is involved in Pepeto, and that fear surrounding ETF holdings has pushed more capital into the presale.

Pepeto operates a direct trading platform allowing swaps without fees and without the spreads typically charged by major exchanges.

The project also includes a risk evaluation tool that scans token smart contracts before purchases are executed, aiming to protect investor capital from fraudulent projects that drain digital wallets.

Its system connects multiple blockchain networks to allow token transfers across chains in a single step, reducing additional costs that often impact smaller investors.

Pepeto also offers staking yields reaching 173% annually, alongside expectations of a future Binance listing, which could add compounded rewards on top of entry pricing.

The development team reportedly includes a former Binance expert, a factor the project says strengthens the potential for strong trading volumes once listed. Smart contracts have also been audited by SolidProof.

The current presale price stands at $0.0000001864, while the total supply amounts to 420 trillion tokens, matching the same supply structure used by the original Pepe token before it reached multi-billion-dollar valuations.

According to the project, wallets investing now have already calculated the risks and are betting on what a token linked to the Pepe founder and backed by real trading tools could achieve after official listing.

Bitcoin price outlook

Bitcoin traded near $81,400 on May 14 after breaking below the $80,000 support level that had held for six weeks, according to CoinMarketCap data.

The 200-day moving average at $82,228 confirmed that sellers remain in control of the short-term trend after rejecting price advances four separate times.

The main support level currently stands at $75,800, which was the area that launched April’s rally.

Meanwhile, a close above the $82,000 level could reopen the path toward $85,000 initially, followed by the $88,000–$92,000 range.

Bitcoin’s all-time high remains at $126,198, recorded in October 2025, representing a potential upside of around 58% from current levels, meaning a $1,000 investment could theoretically grow into $1,580.

The report compares this with low-priced presale projects, where a single listing event can completely reprice the token within a short period.

Bitcoin continues dominating headlines, but with its market capitalization now at $1.3 trillion, the report argues that the massive life-changing returns seen in earlier market cycles have become harder to achieve.

It suggests that larger opportunities may now lie in projects still trading at pre-listing prices, backed by actual operational tools, and still accessible to investors closely watching the market.

According to the report, more than $10 million has already flowed into Pepeto from investors who believe they entered ahead of the broader market’s confirmation of the next major trend.