Ask any cook who has transitioned from conventional techniques to sous vide and they will tell you the same thing: the results are not incrementally better – they are categorically different. A steak cooked sous vide does not merely taste good. It achieves a texture and moisture level that high-heat cooking cannot replicate without extraordinary luck and skill. Understanding why requires a closer look at what is actually happening inside that sealed bag and warm water bath, and what that means for anyone – professional chef or dedicated home cook – who wants to consistently produce exceptional food.

The Science Behind the Method

Sous vide – French for “under vacuum” – describes a process in which food is sealed inside a bag with the air removed and then submerged in a water bath held at a precise, stable temperature. That temperature is typically far lower than what a conventional oven or stovetop burner produces. A medium-rare steak, for instance, might cook at 130°F to 132°F – temperatures at which a conventional oven would barely register as warm. But held there for the right amount of time, the meat reaches that exact internal doneness from edge to center, uniformly.

The physics are straightforward. Water conducts heat far more efficiently than air, so the bag’s contents respond quickly and precisely to the bath temperature. Because the water never exceeds the target – unlike an oven where ambient heat can climb hundreds of degrees above the food’s ideal internal temperature – overcooking becomes structurally impossible. The food can only reach the temperature of its environment, and that environment is the exact temperature you want the food to be.

Why Texture Changes So Dramatically

Texture in cooked food is largely a function of protein denaturation and moisture retention. When proteins are exposed to high heat rapidly, they contract aggressively, squeezing out moisture and becoming firm or rubbery. This is why a chicken breast cooked quickly at high heat often feels dense and dry even when the center reaches the correct temperature – the exterior has already overcooked by the time the heat penetrates inward.

Sous vide at lower temperatures allows proteins to denature gradually and more gently. Muscle fibers relax rather than seize. Collagen in tougher cuts has time to convert to gelatin without the surrounding muscle drying out. The result is a texture that is simultaneously tender and succulent – something that high-heat cooking achieves only inconsistently and only in the hands of experienced cooks who have spent years developing an instinct for timing. With sous vide, that outcome is reproducible by anyone who follows the temperature and time parameters correctly.

How Different Ingredients Respond

Proteins are the most obvious beneficiaries, but the method’s advantages extend well beyond meat and fish into many sous vide products. Each ingredient category responds to sous vide in its own distinct way, and understanding those responses helps cooks unlock results that conventional techniques struggle to match.

Red meats cooked at controlled low temperatures achieve the uniform pink interior that defines a proper medium-rare, with no gradient of gray from the outside in. Poultry, which carries food safety requirements that often lead to overcooking with conventional methods, can be cooked to a safe internal temperature that still feels moist and tender rather than chalky. Fish – notoriously difficult to cook perfectly under direct heat – holds its delicate structure and natural moisture at precise low temperatures, achieving a translucent, silky quality that pan-searing rarely produces.

Vegetables respond differently but no less dramatically. Cooked in a sealed bag at temperatures just below boiling, they retain cellular structure, color, and nutrients that water-based cooking methods leach away. A carrot cooked sous vide tastes more intensely of carrot than one simmered in a pot, because nothing escapes the sealed environment. Eggs, placed directly in their shells into a precisely tempered bath, achieve custard-like textures that boiling or steaming cannot replicate – a fully set white surrounding a yolk that is warm, thick, and creamy rather than chalky.

The Practical Advantages for Professional Kitchens

The quality argument for sous vide is compelling on its own, but it becomes even stronger when layered with operational advantages. In a professional kitchen, producing a superior product is only valuable if it can be done reliably, at volume, across every service. Sous vide addresses all three requirements simultaneously.

Because the method is hands-off once food enters the bath, a single cook can oversee multiple items cooking simultaneously without actively managing each one. Production can happen in advance – proteins cooked during prep, chilled, and held until service – so the line operates as a finishing station rather than a full cooking operation during peak hours. That shift reduces errors, speeds ticket times, and allows kitchen teams to focus creative energy on plating and presentation rather than monitoring cook temperatures.

For high-volume kitchens managing consistency across a full service team with mixed experience levels, the standardization is transformative. A junior cook finishing a precision-cooked protein correctly delivers the same result as a senior chef doing the same thing. The water bath has already done the hard work. Quality becomes a function of process rather than individual talent, which means it scales.

Bringing Sous vide Into Your Kitchen

For kitchens new to the method, the barrier to entry is lower than it might appear. The core equipment – an immersion circulator and a vessel large enough to hold a water bath – is widely available and relatively affordable at the entry level. Vacuum sealing equipment, which provides the best results and extends refrigerated shelf life, requires slightly more investment but is standard in most professional kitchen environments already.

Operators who want to capture the best sous vide solutions without building full in-house production infrastructure can also work with suppliers who specialize in precision-cooked components. Pre-cooked proteins and vegetable preparations arrive ready to finish and plate, delivering consistent quality across every service without requiring dedicated equipment or the learning curve of developing in-house protocols. Whether the approach is fully in-house, fully sourced, or a hybrid of both, the quality floor that sous vide establishes is significantly higher than what conventional methods can sustain at scale.

The technique that was once exclusive to Michelin-starred kitchens is now accessible to any operation willing to invest in understanding how it works. For those who take the time, the results speak clearly: better food, more consistently, with less waste and less effort. That combination is difficult to argue against.

Methylene Blue has moved from being a niche compound discussed mainly in research circles into something people interested in brain health and longevity are actively paying attention to. Not because it promises miracles. But because the underlying mechanisms are biologically interesting and grounded in cellular energy, specifically how mitochondria function. If you care about cognitive performance long term, you eventually end up talking about energy metabolism inside brain cells. That’s where Methylene Blue enters the discussion. This article looks at Methylene Blue as a longevity compound for brain health and cellular energy     , and why some researchers think it may also connect to long-term metabolic health.

Methylene Blue and the Brain: Starting at the Cellular Level

Brain performance depends on energy availability. Neurons consume large amounts of ATP, the molecule responsible for cellular energy transfer. When ATP production drops, people may notice slower processing speed, poor focus, or mental fatigue.

Methylene Blue appears to act directly on mitochondrial function, specifically the electron transport chain involved in energy production. Research suggests the compound may help mitochondria operate more efficiently by assisting electron transfer during oxidative phosphorylation. That means more consistent ATP production under certain conditions.

According to research summarized on AgelessRx¹, Methylene Blue can enter compromised mitochondria and support energy production pathways that may otherwise slow with age or oxidative stress.

That matters because mitochondrial decline is often associated with:

• Brain fog
• Reduced cognitive resilience
• Slower memory formation
• Neurodegenerative risk factors

Instead of acting as a stimulant in the traditional sense, Methylene Blue is being studied as a metabolic enhancer, potentially improving how brain cells generate energy rather than forcing activity through neurotransmitter manipulation.

Cognitive Enhancement Through Mitochondrial Support

Many nootropics focus on neurotransmitters like dopamine or acetylcholine. Methylene Blue takes a different path.

Research indicates² that improved mitochondrial efficiency may influence:

• Synaptic plasticity
• Neural signaling efficiency
• Cerebral blood flow
• Oxygen utilization in brain tissue

Instead of pushing the brain harder, the compound may help optimize energy use at the cellular level.

For people experiencing mental fatigue, poor focus during prolonged tasks, or difficulty sustaining cognitive performance, targeting mitochondrial function can be appealing because it addresses underlying energy availability rather than symptoms alone.

Methylene Blue Benefits Dosage: Why Protocol Matters

One of the biggest mistakes people make when researching methylene blue is assuming more is better. That approach misses how dose-dependent the compound appears to be.

Low doses are often discussed for potential cognitive or metabolic support. Higher doses historically served medical uses such as treatment for methemoglobinemia, an FDA-approved indication.

Several factors influence how dosing strategies are structured:

• Body weight
• Medication interactions
• Individual metabolic response
• Clinical supervision

AgelessRx outlines structured protocols where methylene blue capsules are typically taken with medical oversight, rather than daily high dosing.

Why does this matter?

Because mitochondrial signaling can follow a hormetic response curve, meaning lower amounts may support adaptive processes, while excessive exposure could produce the opposite effect.

Another common mistake: using liquid dye forms sourced outside medical channels. Capsules avoid staining issues and allow more consistent dosing accuracy.

Historical Context: Why Researchers Keep Studying This Compound

Methylene Blue is not new. Synthesized in the late 1800s, it has been used medically for more than a century and appears on the World Health Organization’s essential medicines list due to its established therapeutic uses.

That long history means scientists already understand many aspects of its pharmacology, which lowers barriers to exploring new applications.

Research areas continue to include:

• Neuroprotection
• Age-related cognitive decline
• Mitochondrial dysfunction
• Oxidative stress modulation

Laboratory studies suggest Methylene Blue may act as both an antioxidant and a redox cycling agent depending on concentration and cellular context.

That dual behavior is one reason longevity researchers remain interested.

Memory, Focus, and Mental Clarity: What Mechanisms Are Proposed?

Several mechanisms are frequently discussed when evaluating cognitive enhancement potential:

1. Improved ATP Availability

Higher cellular energy availability may support sustained neural activity. Neurons require constant energy supply, and mitochondrial inefficiency is linked with cognitive fatigue.

2. Increased Cerebral Blood Flow

Some studies suggest improved oxygen delivery to brain tissue, which may support memory processes and executive function.

3. Reduced Neuroinflammation

Inflammatory signaling in the brain is associated with mental fog and slower processing speed. Early research indicates Methylene Blue may influence inflammatory pathways, though outcomes vary depending on context.

4. Oxidative Stress Modulation

Oxidative damage accumulates with aging. Compounds that interact with mitochondrial redox processes may help maintain cellular balance.

These mechanisms do not guarantee outcomes. But they provide a biological explanation for why some individuals report improved clarity or focus during structured protocols.

How Methylene Blue Compares to Traditional Nootropics

Traditional nootropics often target neurotransmitter pathways directly, caffeine increases alertness through adenosine receptor activity, while racetams influence glutamate signaling.

Methylene Blue differs because its primary action appears metabolic.

According to AgelessRx discussions² comparing the compound to standard cognitive enhancers, the potential advantage lies in supporting underlying cellular processes rather than temporarily altering brain chemistry.

This difference may explain why some people describe effects as subtle but stable instead of fast and dramatic.

Mitochondria, Brain Health, and Long-Term Metabolic Function

Brain health and metabolic health are not separate topics.

Mitochondrial dysfunction plays a role in:

• Insulin signaling
• Inflammatory pathways
• Cellular aging processes

If a compound influences mitochondrial efficiency, researchers naturally explore broader metabolic implications.

For example:

• Improved cellular respiration may help cells respond better to metabolic stress.
• Enhanced energy utilization may support resilience against age-related decline.

That doesn’t mean Methylene Blue directly treats metabolic disorders. But mitochondrial health sits at the intersection of brain function and systemic longevity discussions.

Methylene Blue Capsules: The Science Behind Energy, Focus, and Neuroprotection

One thing often overlooked when discussing compounds like Methylene Blue is sourcing and clinical oversight. The difference between pharmaceutical-grade formulations and unregulated alternatives is significant, not just in purity but in dosing precision. AgelessRx structures access through licensed providers who evaluate candidates before prescribing and provide monitored protocols rather than open-ended use. The capsules are produced through certified pharmacy channels and designed for consistent absorption without exposure issues that liquid forms may introduce. That combination, authenticated sourcing plus physician-guided titration, reduces the risk of people experimenting blindly with dosages while allowing individuals interested in cognitive longevity strategies to follow structured guidance backed by medical review.

Mitochondrial Support as a Cognitive Strategy

Methylene Blue sits at an interesting intersection between neuroscience and metabolic biology. Instead of targeting a single neurotransmitter, the focus shifts toward energy production, the foundation that allows brain processes to function efficiently.

For individuals exploring methylene blue capsules as part of a longevity approach, the discussion should stay grounded in realistic expectations:

• Potential support for mitochondrial function
• Possible improvements in memory or focus for some individuals
• Structured dosing protocols under medical supervision

The bigger takeaway is that cognitive enhancement may not always be about pushing the brain harder. Sometimes the conversation turns toward helping cells produce energy more effectively, and that’s where Methylene Blue continues to attract scientific attention.

1-https://agelessrx.com/methylene-blue-for-energy-longevity-a-deep-dive/

2-https://agelessrx.com/methylene-blue-vs-traditional-nootropics-what-you-need-to-know/

2025 was the year technology stopped being tomorrow’s promise and became today’s anchor. What began as a surge in generative AI and platform innovation two years prior crystallized this year into concrete shifts in how people work, governing bodies legislate, and markets invest. Across continents and industries, the arc of technology bent toward practical impact, regulatory reality, and economic weight.

At the heart of the year’s story was artificial intelligence’s jump from novelty to infrastructure. LLMs and multimodal models moved beyond demos into everyday workflows, influencing how documents are written, campaigns are conceived, products designed, and code generated.

Enterprises that once hesitated began deploying AI tools at scale, with early adopters reporting measurable productivity gains by integrating copilots into core processes, a trend visible in surveys showing widespread adoption among software professionals.

This editorial isn’t a chronicle of every press release.

It’s a reflection on how 2025, at the crossroads of technology, governance, and economic strategy, brought about a series of inflection points that will shape the next era of creation, competition, and control.

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When imagination became infrastructure

OpenAI’s release of GPT-5 in August pushed the boundaries of what AI could do, delivering notable gains in coding, math, and multimodal understanding. But unlike the jaw-dropping debut of ChatGPT a couple years prior, this new generation of foundation models arrived to a more measured reception.

Tech leaders and investors had begun asking harder questions: beyond impressive demos, could these models drive real products and revenue?

Google’s answer was Gemini 3, launched in November as its “most intelligent model” and immediately woven into Google’s flagship product, Search. For the first time, an AI model upgrade wasn’t just about boastful leaderboard scores, it was about transforming user experience.

Typing a query into Google now often meant receiving an AI-generated synthesis instead of the familiar list of links, a sea change in how information is delivered. Google even unveiled a Gemini “agent” that could execute multi-step tasks like booking travel or organizing email, hinting at a future where AI acts more like a digital butler than a chatbox.

Anthropic’s Claude 4 model, for instance, gained a strong following among developers by expanding how much it could handle at once, processing entire codebases with tens of thousands of lines, rather than by producing viral one-liners.

AI grew up in 2025: it was still improving at breakneck speed, but it also had to earn its keep in real products and justify the billion-dollar bets fueling its rise.

Chips and Gadgets

Driving this AI explosion was a parallel leap in hardware. The hunger for AI computers in 2025 was insatiable, and chipmakers raced to deliver.

NVIDIA, whose GPUs had become the era’s essential infrastructure, rolled out its new Blackwell architecture with chips like the B200 that boasted up to 3× the training speed of its predecessor. Cloud data centers around the world scrambled to deploy these to keep up with demand from model training and inference.

Rival chipmakers weren’t idle either: AMD and a cadre of startups pushed innovative AI accelerators, while even Intel signaled ambitions to catch up, reportedly exploring an acquisition of AI chip designer SambaNova.

Perhaps most tellingly, tech giants themselves started designing silicon tailored for AI workloads, recognizing that owning the chip means owning the future of computing.

Beyond AI chips, consumer hardware saw its own milestones. After years of anticipation, augmented reality glasses and mixed-reality headsets finally had their moment, sort of.

Apple’s Vision Pro headset, unveiled in late 2023, reached select markets in 2024; by 2025 developers were crafting the first wave of immersive apps. However, mass adoption lagged due to the device’s sky-high price and bulky format.

Competitors like Meta’s Quest line offered cheaper VR headsets and modest improvements, but the “metaverse” hype of yesteryear largely fizzled out, users and investors had shifted their excitement to generative AI and tangible productivity tools.

Smartphones and laptops in 2025 continued incremental improvements (faster Apple M3/M4 chips, foldable screens becoming more common), yet it was clear the next paradigm shift in personal tech was still on the horizon.

Even so, one hardware frontier made concrete progress: quantum computing. Industry leaders like IBM and Google demonstrated prototype systems with ever-larger qubit counts and made strides in error correction, inching closer to viable quantum machines.

These advances, while esoteric to the public, underscored a broader theme, from AI accelerators to quantum chips, the machinery under the hood of tech was evolving rapidly to enable the software of tomorrow.

Regulators strike back

If 2025 proved anything, it’s that technology no longer operates above the law. This was the year regulators moved from intent to enforcement, with Europe leading the charge.

After years of debate, the EU’s Artificial Intelligence Act came into force, becoming the world’s first complex AI law. From February, certain “unacceptable risk” uses, such as social scoring and real-time biometric surveillance, were banned outright.

By August, transparency rules followed, forcing companies to label AI-generated content and comply with new obligations for general-purpose models. The signal was unmistakable: in Europe, the era of unchecked AI was over.

Companies now face audits, penalties, and real consequences if their systems cross legal or ethical lines, a regulatory moment European officials openly compared to GDPR’s impact on data privacy.

The pressure didn’t stop with AI. In 2025, regulators also went after the gatekeepers. The EU’s Digital Markets Act forced long-resistant changes from Big Tech, most notably when Apple opened the iPhone to third-party app stores and sideloading in Europe, dismantling a 15-year walled garden.

At the same time, enforcement of the Digital Services Act intensified. Platforms were scrutinized for how they handle disinformation, with companies like X warned or penalized during periods of geopolitical tension. In response, social networks expanded moderation teams, adjusted algorithms, and exposed more of their inner workings to researchers.

Elsewhere, governments followed suit.

The US issued an AI executive order and signaled tougher enforcement through agencies like the FTC, while states stepped in, including New York’s law requiring mental-health warnings on addictive social features.

In China, new draft rules targeted AI systems designed for human-like interaction, tightening licensing and ideological oversight. By the end of the year, the freewheeling phase of tech disruption had given way to something more restrained. The question was no longer whether regulation would catch up, but how deeply it would reshape innovation itself.

Platforms pivot & users change course

The platform shake-up that began in 2023 gathered real momentum in 2025, as both companies and users adjusted to a post-pandemic, AI-saturated reality.

Nowhere was this clearer than in social media. Elon Musk’s X, which entered the decade with noise and bravado, found itself on the defensive. Meta’s Threads, initially dismissed after an early spike, steadily closed the gap, nearing parity with X in daily mobile users by mid-year.

X’s audience shrank as policy whiplash and leadership churn eroded confidence, and while its remaining users were still deeply engaged, the era of unquestioned Twitter dominance was over. Disenchanted users scattered across a fragmented landscape, from Meta’s polished Threads to decentralized alternatives like Bluesky and Mastodon, breaking the old Facebook–Instagram–Twitter equilibrium.

The recalibration extended well beyond social feeds.

Major platforms retooled around changing habits: Google reshaped Search around generative answers to fend off AI assistants and algorithmic discovery, while Microsoft pushed its Copilot deeper into Windows, Office, and Bing, betting on “AI inside” as a platform reset.

Everyday behavior shifted too. Smarter voice and chat assistants returned to daily use, handling emails, refunds, and scheduling with little friction. At the same time, screen fatigue set in. Digital-detox travel gained traction, and younger users gravitated toward apps that promised less algorithmic pressure and more human curation. Even streaming came full circle.

After years of fragmentation, providers began rebundling services, offering combined video, music, and gaming packages that looked suspiciously like cable TV reborn, a reminder that while technology moves forward, user preferences often move in cycles.

Society grapples with tech’s consequences

Amid the gains and momentum, 2025 also became a year of reckoning. As AI systems spread, society began grappling with their cultural and ethical cost. Creators who once marveled at generative tools started pushing back, arguing that their work had been absorbed without consent or compensation.

A wave of lawsuits moved through US courts, with authors accusing companies like OpenAI, Meta, and Google of scraping books and articles to train models. By year’s end, the message was unmistakable: if AI is built on human creativity, many believe its rewards can no longer flow in one direction alone.

Public trust in technology was also tested by a rise in malicious uses and misuses. In the financial domain, sophisticated deepfake scams caused real damage. The frequency of such incidents spiked sharply; cybersecurity firms reported a 3000% increase in deepfake-related fraud over two years, and authorities scrambled to educate businesses on new verification practices.

Misinformation continued to be a menace: during elections and conflicts, AI-generated fake images and videos spread on social media, forcing newsrooms to set up rapid-response fact-checking teams.

Encouragingly, 2025 also saw growth in countermeasures, from better deepfake detection algorithms to nascent standards for cryptographic content authentication (the Coalition for Content Provenance, including major publishers and tech platforms, expanded efforts to watermark authentic media).

Still, the information ecosystem remained fraught, as even savvy citizens found it ever harder to tell the truth from fabrication online.

And then there’s the human element: how all this tech is affecting everyday lives and livelihoods. Workplace AI adoption soared this year; tools like Microsoft 365 Copilot and a host of AI assistants became common on office desktops. Studies showed productivity boosts but also raised concerns about workers becoming overly reliant on AI suggestions.

Meanwhile, fears of automation resurfaced in certain sectors, for example, as chatbots took over more customer service and code-generation tools improved, professionals in call centers and junior programming positions wondered about long-term job security.

These anxieties fueled calls for new approaches to education and training, so that the workforce of 2030 will be prepared for more creative, complex tasks that AI can’t easily handle.

The editor’s verdict: Lovable wins 2025

Lovable (Stockholm, Sweden) came as one of the most remarkable AI software stories of the year, for me. What began as an open-source project evolved into a commercial platform that lets users build fully functional websites and apps using plain-language prompts, no traditional coding required.

This approach, known in the industry as “vibe coding,” turns ideas into production-ready software simply by describing what you want in natural language.

Lovable’s growth in 2025 was extraordinary by any measure. Eight months after its launch, the company hit over $100 million in annual recurring revenue and raised a $200 million Series A at a roughly $1.8 billion valuation, making it one of Europe’s fastest-growing software startups ever.

By year’s end, Lovable had secured $330 million in Series B funding at about a $6.6 billion valuation, and was rapidly scaling globally.

What makes Lovable meaningful beyond the numbers is what it represents: a shift in how software is built. It demonstrated that AI can democratize development, giving power to non-technical founders, creators, and teams to go from concept to product without traditional engineering barriers.

In an industry long centered on specialized skills and team structures, Lovable’s rise suggested a future where natural language becomes the primary interface to software creation.

On a more hopeful note, 2025 showed signs of a maturing tech culture. Ethical design moved from talking point to practice. Major platforms began experimenting with limits, turning off infinite scroll for teens, adding prompts that nudged users to pause, and treating “time well spent” as a real metric rather than a slogan.

In AI, transparency gained ground. Under pressure from regulators and researchers, companies like OpenAI and Google disclosed more about how their models are trained and where they fall short.

Researchers formed new alliances to share safety techniques, and a second global AI Safety Summit brought dozens of countries together around questions of alignment and control.

None of it amounted to binding rules, but it marked a shift in tone: even the architects of powerful systems openly acknowledged the need for restraint.

Taken together, these moments made 2025 a turning point. For years, technology had surged ahead of the institutions meant to guide it. This year, that gap began to close.

The breakthroughs were real and transformative, but so were the responses to them: laws passed, norms reset, alliances formed. If 2024 was the year the world grasped the power of generative AI, 2025 was the year it began deciding how that power should be used.

The story of technology is no longer just about what can be built, but about how it fits into the lives it shapes, and who gets to decide that fit.

Labor market weakness, inflation uncertainty and political pressure will prompt the Federal Reserve to aggressively cut interest rates in early 2026, according to Mark Zandi, chief economist at Moody’s Analytics.

Although markets and Fed officials themselves expect only modest easing next year, Zandi expects the central bank to make three cuts of a quarter of a percentage point each before midyear.

“The still weak labor market, especially at the beginning of 2026, will be behind the decision to further loosen monetary policy,” the economist wrote in his recently published outlook for the coming year. “It will take longer for companies to be confident they won’t be caught off guard by changing trade and immigration policies and other threats before they start hiring again.”

“Until then, job growth will not be enough to prevent further increases in unemployment, and as long as unemployment rises, the Fed will cut interest rates,” he added.

Zandi’s forecast is at least a step above market and Fed expectations, both of which point to a slower pace of cuts.

Market prices are currently pointing to two cuts, with the first coming in April at the earliest and the second more likely in the second half of the year, probably around September, according to CME futures data expressed through the FedWatch indicator system.

Fed policymakers have an even more cautious outlook.

The grid of expectations from individual central bank officials only points to a full-year decline, according to an update provided in early December. Minutes from that meeting indicated the cut was a close call, with officials expressing the likelihood of further cuts, but only at a measured pace.

But Zandi believes the confluence of these factors will cause the Fed to respond more quickly. A wild card: the potential for President Donald Trump to reshape the central bank hierarchy.

As things stand, three of the seven Fed governors are Trump appointees: Christopher Waller, Michelle Bowman and Stephen Miran. With Miran’s term expiring in January, Trump is likely to appoint another loyalist to the post. From then on, Chairman Jerome Powell’s term at the helm ends in May, although his term as governor ends in early 2028. In addition, the president is trying to remove Governor Lisa Cook, although the courts have so far blocked him.

This increases the likelihood that the president, a staunch supporter of lower interest rates, will try to exert his will on the Federal Open Market Committee, which sets interest rates.

“Trump will also push for lower interest rates. The Federal Reserve’s independence will steadily erode as the President appoints more members to the Federal Open Market Committee, including the Fed Chair in May,” Zandi wrote. “With the congressional midterm elections approaching, political pressure on the Fed to further cut interest rates to support economic growth is likely to increase.”

The FOMC meets again on January 27th and 28th. According to CME, the probability of a cut at this meeting is only 13.8% based on market prices.

A graph showing the Apple stock price in a smartphone app.

Jaap Arriens | Photo only | Getty Images

Retail investors had a disastrous year in 2025.

Mom-and-pop investors bought at key points of decline this year, driving strong returns as the market climbed to all-time highs. A new generation of retail investors, once considered unsophisticated and easily deceived, is giving competition to the professionals who long rejected them, according to investors and market data analysts interviewed by CNBC.

“Retail is getting smarter and it’s getting tougher on the market,” said Mark Malek, head of investments at Siebert Financial. In other words, these investors are really “growing up.”

Individual traders were quicker to buy the decline during market declines earlier in the year, according to JPMorgan Quant analyst Arun Jain, who called it a “successful year” for this group. It was an effective strategy: 2025 is shaping up to be the second-best year for dip buying since at least the early 1990s, according to data released this month by Bespoke Investment Group.

According to JPMorgan, starting in May, these investors shifted their focus from individual stocks to ETFs. The group was particularly concerned with SPDR Gold Shares (GLD) JPMorgan noted that inflows in 2025 exceeded those of the previous five years combined. The gold-focused ETF has posted a record-breaking gain of more than 65% this year as the precious metal rose to all-time highs.

The result: According to data the bank released earlier this month, retail investors’ individual stock portfolios posted higher profit-loss ratios than baskets tied to artificial intelligence and JPMorgan-powered software. Everyday investors’ exchange-traded fund holdings had much higher win rates than that SPDR S&P 500 ETF Trust (SPY) And Invesco QQQ Trust (QQQ)the company noted.

Buy “TACO” and the dip

A key driver of their strong performance this year dates back to a week in April that left investors of all sizes on tenterhooks.

Big money came crashing down when President Donald Trump first unveiled his plan for sweeping, high tariffs on most foreign countries on April 2, which he dubbed “Liberation Day.” The S&P 500 briefly fell into bear market territory as institutional investors feared the policy would drive up inflation and weigh on corporate earnings.

But small investors plunged headfirst into the turbulence. According to VandaTrack, they made a record net purchase of more than $3 billion in stocks on April 3 – even though the S&P 500 fell about 5% in the session. The increased buying continued the following day, although the benchmark average fell another 6%.

On April 9, exactly one week after “Liberation Day,” Trump put most of his key duties on hold. Small shareholders were on the ground floor of the S&P 500’s 9.5% rise this session. The broad index is up more than 21% since April 2. It is on track to end 2025 up more than 17% after hitting several new intraday and closing records.

“We often talk about retail being a little late to the party,” said Viraj Patel, Vanda’s deputy head of research. “But that was the exact opposite.”

Stock chart iconStock chart icon

S&P 500, year-to-date

At Siebert, Malek said professionals were starting to get nervous as the S&P 500 fell below 5,000 during the tariff-related selloff. However, its retail traders continued to buy until the end of the session, capitalizing on their previous successes in increasing exposure amid setbacks rather than panicking.

Retail investors “were more right about the market and how to react to many of the year’s emotionally charged trades,” Malek said. “They were much more precise in their dealings than my colleagues in the institutional sector.”

These traders not only believed in buying on dips, but also benefited from the belief that “TACO trading” would be successful, according to Zhi Da, a professor of finance at the University of Notre Dame whose research focuses on the activities of retail traders.

Read more about CNBC’s retail investor coverage

This strategy, known in full as “Trump Always Chickens Out,” encourages investors to buy into stocks when White House policy decisions lead to market downturns in anticipation of the policies reversing. On the other hand, institutional partners have been more cautious about circumventing Trump’s policies, Da said.

He acknowledged that there was some luck involved and that 2025 was an “exception” to the rule. Typically, retail investors buy market declines too late and don’t benefit as much on average, he said.

A more “sophisticated” investor

The positive 2025 for retail comes one year after the investment boom among Americans that began during the pandemic. The next severe market downturn will test whether the increased participation will last.

In 2024, more than one in three 25-year-olds have transferred significant amounts from checking to investment accounts since turning 22, according to JPMorgan data released earlier this year. That’s up from just 6% of 25-year-olds in 2015.

JPMorgan noted that retail flows reached record highs in 2025, up more than 50% from the previous year and about 14% higher than the meme stock boom of early 2021. The share of individual investors in total trades climbed this year to highs last seen during the short-squeeze mania four years ago, according to data from a working paper by professors at Chapman University, Boston College and the University of Illinois Urbana-Champaign emerges.

The narrative during the meme stock boom in 2021 – which focused on stocks like GameStop And AMC – was that private investors made simplified investment decisions in order to “leave it to the man.” Two years later, the sentiment toward these meme-stock-era investors was captured in a film starring Pete Davidson, Seth Rogen, and Sebastian Stan called Dumb Money.

Vandas Patel and others said perspectives are changing. Retail investors are taking advantage of expanded access to market research and data — and gaining a better reputation on Wall Street as a result, they said. Retailers have also proven more adept at buying at low prices and are increasingly comparable to larger rivals, Patel said.

“The average retail investor is becoming more sophisticated,” Patel said. “This year was a good example of that.”

A scene from the trailer for the film: Dumb Money

Courtesy: Sony Pictures Entertainment

Of course, there is also a new class of meme stocks OpenDoor was created this year. But Vanda found that in 2025, far more retail investor money has flowed into names like… Nvidia, Tesla And Palantir which has outperformed the market in recent years.

Siebert’s Malek said he has noticed that everyday investors are increasingly focused on longer-term investments, which can save them from panic selling when the market falls. Still, one question remains top of mind for Malek and other investment managers: What will retailers do when the stock market finally enters a sustained period of trouble after several years of big gains?

For now, private investors are taking note of their improved position.

Real estate professional Josh Franklin remembers a decade ago when they were easily written off by major investors. The 28-year-old Tampa resident who has invested in stocks like Robinhood and Palantir over the years, spending dozens of hours a week studying the market, now sees the little guy as a central part of the story.

“Back then, no one really cared about retail. They thought retail was dumb money,” Franklin said. “Retail is now at the top of the charts, so to speak.”

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By Paul D. Thacker

The panic and outrage were palpable last February when President Trump announced plans to trim reimbursement rates for government-funded scientific research.

“This is going to decimate U.S. scientific biomedical research,” Northwestern University biologist Carole Labonne told Bloomberg. “The lights will go out, people will be let go, and these [medical] advances will not occur,” David Skorton, CEO of the Association of American Medical Colleges, told PBS. “The goal,” University of Washington biologist Carl Bergstrom warned on BlueSky, “is to destroy U.S. universities.”

The sky has not fallen on American research in the 10 months since. The National Institutes of Health (NIH) is still paying the same 50% to 70% in indirect costs – the premium added on top of grants meant to reimburse universities for providing labs and other research infrastructure – because lawsuits have frozen the president’s proposed policy. One Trump official admits this is unlikely to change because the administration will almost certainly lose in court. The current system, which provides the lion’s share of billions of dollars each year for often-unspecified overhead costs to universities, has the backing of Congress. As it stands, there appears to be no momentum, even among Republicans, to reform the practice.

“It’s basically a slush fund,” one NIH official told RealClearInvestigations. “We just don’t like to call it that.”

A RealClearInvestigations analysis of these indirect payments reveals a long, largely forgotten history of concern about taxpayer-sponsored research. Although many researchers have cast Trump’s proposal as an attack on science, this issue isn’t the need to fund research activities that sometimes lead to beneficial discoveries, but whether some of the billions that support the necessary infrastructure and equipment are actually being shifted to purposes such as staffing and buildings that have little or no direct connection to the actual research. 

In the late ’80s, Stanford faculty revolted against the university’s high overhead charges for diverting research dollars to a bloated administration and a campus building frenzy. Those concerns are still voiced by some.

“If the universities truly believe that it takes 60-70% of a research grant to provide facilities, utilities, and other basic support, then that is easy to prove by opening the books,” said Sanjay Dhall, a research physician at the University of California, Los Angeles. “I suspect however, that opening the books would reveal that a significant chunk of these funds, or even the majority, are paying an army of unnecessary administrators.”

At a time when the value of college is being challenged because of exorbitant tuition and fees, and the federal government is struggling to rein in debt, the story of indirect funding offers a window into the history of runaway costs and the growing power of college officials. RCI has also learned that NIH Director Jay Bhattacharya has been selling a new plan that makes the grant process more competitive for institutions that were overlooked in the past. 

Indirect Costs Hard To Define

Distributing over $37 billion in grants every year, NIH is the largest funder of biomedical research on the planet, far exceeding the European Commission, which spends around $12 billion, and dwarfing the Gates Foundation’s $1 billion. 

Every NIH grant a university researcher receives provides two categories of funding: direct and indirect costs. The direct costs include all items the researcher submitted as part of the project’s budget, from laboratory equipment to a percentage of salaries.

Indirect costs are harder to define. The funding goes to administrators, and how they use it is shrouded in mystery. What’s more, indirect rates vary from university to university for reasons that few understand and can explain. 

While institutions charge private foundations like Gates a mere 10% and Rockefeller 15% for indirect costs, they charge the NIH much higher rates – 69% for Harvard, 67.5% for Yale, and 63.7% for Johns Hopkins. 

“How do you think Harvard built all those buildings?” one NIH official, a graduate of Harvard Medical School who insisted on anonymity, told RCI. “NIH indirect costs paid for that.”

When Trump first proposed the 15% cap in 2016, Harvard president Drew G. Faust told the student newspaper in late 2017 that she flew to Washington, D.C., to lobby Republicans in both the House and the Senate to stop it. “We’re bringing in quite a bit of money through federal contracts which provide money for a lot of buildings and other infrastructure that makes possible what we do going forward,” a Harvard dean told the student newspaper. “So if that was to all go away, we’d have to sit down and look at that.”

The Trump administration’s proposal to cap overhead at 15% would cost university administrators billions of dollars that they control. Among the many critics was Holden Thorp, editor-in-chief of the flagship journal Science and a former university administrator. He wrote an editorial last February titled “A Direct Hit” that described the cap as a “ruthless takedown of academia.”

“The scientific community must unite in speaking out against this betrayal of a partnership that has enabled American innovation and progress,” he wrote.

In response to questions from RCI, Thorp said any change to NIH overhead funding should be done in partnership with the scientific community. “Indirect costs are used to secure debt on research facilities and were treated as very secure by banks and the rating agencies,” Thorp said. “Pulling all of that abruptly – without following processes with decades of precedent – is certainly betraying a partnership by putting the universities in difficulty with their lenders and bond ratings.” 

Inexorable Rise in Charges

It turns out that concerns over universities possibly misusing federal grant money date back more than half a century, according to Thorp’s own publication. In 1955, the federal government almost doubled the 8% premium paid for university overhead. A decade later, Science reported that Congress lifted the overhead ceiling to 20%, maintaining a flat rate to assure more taxpayer dollars were targeted at scientific research, and less spent on constructing new buildings. Some members of Congress believed that “the universities need not accept the grants if they can’t afford them.” Elected officials also worried that indirect costs would not go to research but to support other university efforts.

“You might be surprised if you read the list of money being spent for research in various universities,” one senator said in a 1963 Science news story. “Not only to pay the teachers, but also to construct buildings and facilities around the school.” 

Despite these concerns, lobbyists convinced the government in 1966 to remove all caps, empowering universities to negotiate directly with federal agencies to set their own overhead rates. In 1966, overhead consumed 14% of NIH grant expenditures. By the late 1970s, it consumed 36.4%. When the federal government attempted to backpedal in 1976 to bring “spiraling indirect cost rates under control,” it failed. 

Both Republicans and Democrats have long championed increasing NIH budgets, partly because grants for research land in congressional districts scattered across the nation. Republicans have often been the NIH’s biggest supporters. Fifteen years ago, Congress launched investigations into the NIH’s poor monitoring of grants that were awarded to research physicians with undisclosed ties to the pharmaceutical industry. Despite the unfolding scandal, Republican Sen. Arlen Specter pushed through a 34% increase in the NIH’s budget in 2009. During the 2013 government shutdown, the NIH was one of the few agencies that Republicans pushed President Obama to keep open. Two years later, Republicans cut many parts of Obama’s proposed 2015 budget, yet gave the president even more money than the increase he requested for the NIH.

Like some elected officials, academics have also long complained that high overhead harms academic scientists by diverting NIH funding to administrators. In 1981, a University of California researcher published a study in Science, which showed how “Funding has thus been markedly reduced, and this has become a critical factor limiting research support in the United States.”

By 1983, indirect costs accounted for 43% of the NIH grant budget. In response, then-NIH Director James B. Wyngaarden pushed to make more money available for scientists by paying administrators only 90% of what they claimed in overhead. 

“[L]egislators tend to sympathize with the investigators who are more interested in seeing federal money spent for equipment and researchers’ salaries in their labs than for light and heat and the services of typists and bookkeepers,” reported Science at the time. 

However, Science reported that Wyngaarden was met with stiff opposition from university officials and their allies in Congress.

When Wyngaarden tried to deal with the matter by sending a report to Congress, Science reported, officials from several university lobby groups shut the report down, calling it not “acceptable.”

One of Wyngaarden’s biggest critics was Stanford President Donald Kennedy, whose school was then charging one of the highest rates for indirect costs. Kennedy convened a group to attack cost-saving proposals, stating in a letter, “The NIH proposals to reduce reimbursement of those costs … will directly damage the research effort as a whole.” 

This effort appeared to succeed until Kennedy himself became ensnared in a scandal that showed Stanford’s indirect costs charged to the NIH paid for a bevy of personal goods and upkeep on a yacht. 

Stanford’s Taxpayer-Funded Yacht

Stanford’s yacht, the Victoria, was valued at $1.2 million and became a symbol of excess, with walnut and cherry paneling, brass lamps, marble counters, and lavish woodwork. Administrators used the yacht as a fundraising venue to wine and dine campus bigwigs. NIH money had paid for overhead to maintain it. 

As Congress and federal investigators dug into Stanford’s accounting, they discovered that administrators had also redirected NIH research overhead to pay $2,000 a month for flowers at President Kennedy’s home, $7,000 for his bed linens, and $6,000 to provide him with cedar-lined closets. Another college official had hosted Stanford football parties and charged the NIH $1,500 for booze.

Humiliated in the media, Stanford was forced to lower the indirect rate it charged the NIH from 78% to 55.5%, and federal agencies launched audits of overhead charges at dozens of other universities, resulting in millions of dollars returned to the NIH. 

With the politics and the media on his side, Michigan Congressman John Dingell launched reforms to indirect charges. Stanford and other institutions were forced to halt expensive building campaigns. President Clinton proposed a cap on indirect costs in a “concerted effort to shift national spending from overhead to funding research.” As in the past, universities opposed the change, and the White House buckled.

“One way or another, I’ve been involved in controversy about indirect cost rates for about 30 years,” a chancellor at the University of Maryland told The Baltimore Sun in 1994. 

Kennedy resigned from the Stanford presidency, as did several of his administrators. Kennedy later joined Science as editor-in-chief – a predecessor to Thorp – while universities’ charges for indirect costs to the NIH eventually snapped back to their former pricing, which continues to this day.

RCI spoke with several academic researchers at institutions scattered across the U.S., working at both private and public-funded universities. None wished to be named about their concerns about how their administrators spend NIH indirect funding, with one professor noting that administrators determine your career, so it makes no sense to criticize their spending habits.

While university presidents say administrators strictly account for NIH indirect funds, the reality appears to be different. Professors who bring in large sums of NIH money, sometimes referred to as heavy hitters, can complain and get some of the indirect costs back from the administrators for their own research and even personal use. At some institutions, department heads can get a cut of the indirect costs to set up slush funds, monies they can dole out to favored professors, or even divert to their own labs.

Professor Dhall said that after he published a March letter in the Wall Street Journal that supported Trump’s cap on indirect rates, he was contacted by colleagues across the country. “They congratulated me on going public and vehemently agreed, in private,” he said. 

A congressional staffer who has spent decades investigating problems at the NIH said that nobody truly understands how universities negotiate their NIH overhead rates. And once that money gets to the university, it disappears into a byzantine accounting system that seems designed to confuse government auditors, who rarely inspect university books.

“It’s a complete black box,” he said. “I wish someone could explain it to me.”

Trump’s Play To Change the Game

The Trump administration will lose the fight to cap indirect costs at 15%, a senior HHS official told RCI, because of the universities’ outsize influence. During the first Trump administration, universities caught wind that Trump planned to cap overhead rates. As they had done for over half a century, university lobbyists ran to Congress to complain, only now they sought an alliance with the pharmaceutical industry.

Responding to lobbying pressure, Republicans in the House and Senate inserted a provision into the appropriations bill in 2018 to block Trump’s attempt to change universities’ indirect cost rates. That provision has been included in every succeeding appropriations bill.

While it does not seem likely that Congress will strip the schools in their states and districts of billions of dollars in funding, NIH Director Bhattacharya has been floating his own proposal to revamp indirect payments to make them more equitable in private talks with members of Congress and university leaders. Shortly before Thanksgiving, Bhattacharya gave a dinner talk to the Republican Main Street Caucus, a group of 85 GOP members of Congress who are critical behind-the-scenes players among Republicans now running the House. 

A dinner participant recounted to RCI that Bhattacharya noted that more than half of the NIH’s money goes to 20 universities located on both coasts. These elite universities win a lion’s share of the grant money, including indirect costs, because they have the money to attract excellent scientists, in part because NIH money helped them build great infrastructure. 

This creates a vicious cycle that guarantees NIH will continue to fund institutions that have already won past NIH money – and which charge high indirect costs. To end this cycle, Bhattacharya wants to break off indirect costs into a separate category of infrastructure grants that universities can compete to win.

During the talk, Bhattacharya said that all the universities in the entire state of Florida now get as much money as Stanford. Yet, there’s no reason Florida could not become a hub for scientific research if the federal government invested in its scientific infrastructure. 

If Florida can provide lab space at a lower cost than Stanford, he said, they should get the money. Bhattacharya also wants to make it easier for academics to take their grant to different universities. If a Harvard researcher is offered more space or better facilities at a university in Kansas, because building costs there are cheaper, that professor should be able to transfer his grant. 

The NIH already provides specific grants for infrastructure, and the hope is that spreading the billions in indirect costs across the country will gain political support. 

“He wants to get this money out to the middle of the country, not just the coasts,” said Congresswoman Mariannette Miller-Meeks, Republican from Iowa. Dr. Miller-Meeks is one of the few physicians in Congress and said she was impressed with Bhattacharya’s talk at the Main Street Caucus dinner. However, she is uncertain whether Democrats would embrace the new proposal in today’s polarized environment.

“I would think there are members from the center of the country that would like to see more money in their district,” she said.

A spokesperson told RCI that NIH remains focused on ensuring that funding is used efficiently and that direct and indirect costs contribute to scientific productivity. “Bhattacharya’s proposal represents one of several ideas being discussed publicly about how to structure federal support for research infrastructure,” the spokesperson said. “NIH looks forward to continuing to work constructively with Congress on this issue.”

This article was originally published by RealClearInvestigations and made available via RealClearWire.

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Regardless of whether you take photos with the best camera phone or use a real camera, it is almost always impossible to get everything from the foreground to the background in focus. However, a new breakthrough could soon make this a very real possibility.

Researchers at Carnegie Mellon University have managed to develop a new type of camera lens that offers spatially selective focusing, allowing cameras to focus on an entire scene at once. A blog post about the development details that allow this technology to capture photos “where every detail, near and far, is perfectly sharp – from the petal directly in front of you to the distant trees on the horizon.”

Carnegie Mellon University

Unlike traditional cameras, which can only perfectly focus on a flat plane of a scene at a time, the new computational lens uses a mix of optics and algorithms to “adjust focus differently for each part of a scene.”

The resulting system uses two autofocus methods, contrast-detection autofocus (CDAF) and phase-detection autofocus (PDAF), to automatically determine “which parts of the image should be in focus,” essentially giving each part of the image its own focus button.

What this could mean for future cameras

This computational lens has the potential to pave the way for a new range of smartphone cameras that capture sharper photos with less background or foreground blur. The technology also has other potential applications, such as improving how microscopes focus on objects, helping robots and self-driving cars see details from all distances, and making AR/VR much more realistic.

The team presented their results for the first time at the International Conference on Computer Vision earlier this year, where they received the “Best Paper Honorable Mention” award. While the technology is still in the research stage, it will be interesting to see how and when it makes its way into real cameras and consumer devices.

Copper anodes come out of a furnace at the Glencore Canadian Copper Refinery (CCR) in Montreal, Quebec, Canada on Tuesday, August 12, 2025.

Bloomberg | Bloomberg | Getty Images

Copper is on track for its biggest annual price rise in more than a decade, driven by supply disruptions, a weakening U.S. dollar, rising expectations for Chinese economic growth – and blockbuster spending on artificial intelligence.

Analysts expect the red metal’s rally could continue next year, especially amid supply fears and a rapidly expanding global data center footprint.

Three-month copper prices on the London Metal Exchange (LME) rose 1.5% to $12,405 a tonne on Tuesday, erasing recent gains after hitting a record high of $12,960 in the previous session.

The benchmark contract, which has gained about 41% this year, is on track for its best year since 2009, when it gained more than 140% as it emerged from the global financial crisis.

In New York, copper prices have risen more than 40% since the start of 2025, on track for their biggest annual gain since 2009, when the contract rose 137.3%.

Demand for copper is widely seen as an indicator of economic health. The base metal is crucial to the energy transition ecosystem and is an essential part of the production of electric vehicles, power grids and wind turbines.

In fact, electrification, grid expansion and data center expansion require large amounts of copper for cabling, power transmission and cooling infrastructure.

Ian Roper, commodities strategist at Astris Advisory Japan KK, cited a global boom in AI demand as the latest driver for copper prices, with “very tight” markets likely meaning the red metal could rise even further next year.

“The story for copper in recent years has been green energy, right? Even though China has seen a huge real estate downturn.” [and] “That impacts things like steel demand and iron ore prices, but it doesn’t have as much of an impact on copper,” Roper told CNBC’s Dan Murphy on Dec. 23.

“Copper has been a big beneficiary of the expansion of renewable energy and electric vehicles, and now of course data centers are the big growth story,” he added.

AI and defense

Analysts at JPMorgan said in a research note published in late November that LME copper prices could rise even further next year, forecasting an average of $12,500 a tonne for the second quarter.

The Wall Street bank said it expects copper to cost an average of $12,075 by 2026, calling growth in data center demand an “extremely current” upside risk.

“All in all, we believe these unique dynamics of disjointed inventories and acute supply disruptions exacerbating the copper market are driving bullish sentiment for copper and will be enough to drive prices above $12,000 per ton in the first half of 2026,” Gregory Shearer, head of base and precious metals strategy at JPMorgan, said in the note.

Coils, wound copper wires, lie on pallets in the wire mill (coiler) of Aurubis AG. After a casting and rolling process, hot copper wire is wound through the reel into a coil that weighs up to five tons and is around twelve kilometers long.

Picture Alliance | Picture Alliance | Getty Images

However, not everyone is so optimistic about the copper price outlook.

Analysts at Goldman Sachs Research expect copper prices to retreat from recent record highs, even as growing demand for the metal gradually pushes prices higher in the longer term.

In a research note published on December 11, Goldman Sachs Research analysts said LME copper prices are expected to remain in a range of $10,000 to $11,000 as robust global demand growth from the grid and energy infrastructure sector, “supported by investments in strategic sectors such as AI and defense,” prevents prices from falling below $10,000.

Analysts expect LME copper prices to average $10,710 in the first half of 2026. Looking further ahead, they forecast LME copper prices to rise to $15,000 in 2035, noting that this is above industry analyst consensus.

A few years ago, asteroid mining was all the rage. With the commercial space sector growing rapidly, the dream of commercializing space seemed almost imminent. Essentially, the idea of ​​having platforms and spacecraft that could assemble and mine near-Earth asteroids (NEAs) and then return them to space-based foundries was akin to sending commercial crews to Mars. After much speculation and failed ventures, these plans were put on hold until the technology matured and other milestones could first be achieved.

Nevertheless, the dream of asteroid mining and the associated “post-scarcity” future remains. In addition to the need for more infrastructure and technical development, further research is needed to determine the chemical composition of small asteroids. In a recent study, a team led by researchers at the Institute of Space Sciences (ICE-CSIC) analyzed samples of C-type (carbon-rich) asteroids, which make up 75% of known asteroids. Their results show that these asteroids could be a crucial source of raw materials and offer opportunities for future resource exploitation.

The team was led by Dr. Josep M. Trigo-Rodríguez, a theoretical physicist from the Institute of Space Sciences (ICE) and the Catalonian Institute for Space Studies (IEEC) in Barcelona. He was joined by PhD student Pau Grèbol-Tomàs (also from ICE and IEEC), Dr in the *Monthly Communications of the Royal Astronomical Society* (MNRAS).

Reflected light image of a thin section of a carbonaceous chondrite meteorite from NASA’s Antarctic collection. Image credit: ICE-CSIC/JMTrigo-Rodríguez et al. (2025)

Carbonaceous chondrites (C-chondrites) regularly fall to Earth but are rarely recovered by scientists for study. Aside from making up only 5% of all meteorites, their fragility often causes them to shatter and be lost. To date, the majority of specimens found have been found in desert regions, including the Sahara and Antarctica. The Asteroids, Comets and Meteorites Research Group at ICE-CSIC, led by Trigo-Rodriguez, studies the physicochemical properties of asteroids and comets and is the international archive for NASA’s Antarctic meteorite collection.

In this latest study, the research group selected and characterized the asteroid samples, which were then analyzed using mass spectrometry by Professor Jacinto Alonso-Azcárate at the University of Castile-La Mancha. This allowed them to determine the exact chemical composition of the six most common classes of C chondrites and provide valuable information about whether raw material extraction will be possible in the future. Trigo-Rodríguez said in a press release from the Spanish National Research Council (CSIC):

The scientific interest in each of these meteorites is that they sample small, undifferentiated asteroids and provide valuable information about the chemical composition and evolutionary history of the bodies from which they come. At ICE-CSIC and IEEC, we specialize in developing experiments to better understand the properties of these asteroids and how the physical processes occurring in space affect their nature and mineralogy. The work now published is the culmination of this team work.

It is crucial to know the material richness of asteroids because they are very heterogeneous. While they are typically classified into three categories: C-type (carbonaceous), M-type (metallic), or S-type (siliceous), asteroids are also classified by spectral properties and orbit. Furthermore, asteroids are essentially material left over from the formation of the solar system and are heavily influenced by their long evolutionary history (approximately 4.5 billion years). Therefore, it is important to know the exact composition of asteroids to determine where various resources (water, ores, etc.) are likely to be located.

*Source: ESO*

According to the team’s findings, mining undifferentiated asteroids (believed to be the precursor to chondritic meteorites) is far from profitable. The study also identified a type of asteroid rich in olivine and spinel ribbons as a potential target for mining operations. The team also noted that water-rich asteroids with high concentrations of water-bearing minerals should be selected. In the meantime, they emphasize the need for additional sample return missions to verify the identity of the precursor bodies before mining can be carried out. Trigo-Rodríguez said:

In addition to the advances that sample return missions represent, there is an urgent need for companies capable of taking decisive steps in the technological development necessary to extract and collect these materials under low-gravity conditions. The processing of these materials and the waste generated would also have significant impacts that should be quantified and appropriately mitigated.

They argue that this will require the development of large-scale collection systems and methods of extracting resources in microgravity. “For certain water-rich carbonaceous asteroids, extracting water for reuse appears to make more sense, either as fuel or as a primary resource for exploring other worlds,” said Trigo-Rodríguez. “This could also provide science with greater insight into certain bodies that could one day threaten our existence. In the long term, we could even mine potentially dangerous asteroids and shrink them so that they are no longer dangerous.” As Grèbol-Tomàs added:

Examining and selecting these types of meteorites in our clean room using other analysis techniques is fascinating, especially due to the diversity of minerals and chemical elements they contain. However, most asteroids contain relatively small amounts of valuable elements, and therefore the aim of our study was to understand the extent to which their extraction would be useful. This sounds like science fiction, but it also seemed like science fiction to me when the first sample return missions were planned thirty years ago.

In any case, the benefits of asteroid mining are immense, which is why the topic has gained so much attention in the last decade. In addition to precious metals, many asteroids are a source of water ice, which could be used to produce fuel for space missions and water for drinking and irrigating crops. This would mean less reliance on resupply missions from Earth and allow robotic and manned missions to achieve greater self-sufficiency. By moving mining and manufacturing to cislunar space and the main asteroid belt, humanity would also reduce the environmental impact of these industries on Earth.

While public enthusiasm for asteroid mining has waned over the past decade, many companies are now researching and developing the necessary technology. Similarly, space agencies such as NASA and JAXA have conducted sample return missions that revealed much about the scientific and material wealth that asteroids may contain. In the near future, China’s Tianwen-2 mission will rendezvous with a NEA and a major asteroid belt comet. Although it may take many decades (or longer) for a space-based resources industry to emerge, there are many willing to jump in from the start.

Further reading: CSIC, MNRAS

Researchers have unveiled a new AI video generation technique called TurboDiffusion that can create synthetic videos almost instantly. It can generate AI videos up to 200 times faster than existing methods without sacrificing visual quality.

The work is a joint effort between ShengShu Technology, Tsinghua University and researchers at the University of California, Berkeley. According to its developers, the system is designed to dramatically reduce the time it takes to generate video, a process that has traditionally been slow and computationally intensive.

TurboDiffusion sets a new speed benchmark

ShengShu technology

When tested on a consumer PC with Nvidia’s RTX 5090 graphics card, TurboDiffusion reduced the time required to generate a 5-second video clip in standard definition from more than three minutes to just 1.9 seconds. For high-resolution clips of the same length, the time dropped from nearly 80 minutes to just 24 seconds, a roughly 200x improvement.

Current tools like Shengshu’s Vidu and OpenAI’s Sora still require several minutes to create short video clips. Instead of waiting hours for short clips to render, creators could create usable videos in seconds or minutes.

TurboDiffusion can solve a major bottleneck in AI video generation by drastically reducing computation time. This acceleration could enable faster animation, filmmaking and content creation workflows without compromising on quality.

What near-instant AI video means next

Adobe

This breakthrough also suggests that the era of real-time or near-instant AI video creation may be closer than many had expected. But it also raises familiar concerns. Faster video generation may also increase the onslaught of deepfake-style content.

As the production of AI-generated videos becomes faster and more cost-effective, questions about verification, misuse and safeguards are likely to intensify, especially on platforms that already struggle with AI weaknesses.

TurboDiffusion comes as other AI video tools continue to evolve. Google’s Flow Video Creator, which adds richer creative controls, and Adobe’s Firefly, which expands to text-based video editing and native video generation in Premiere Pro, underscore how quickly the market is changing.