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Every day, people are constantly learning and forming new memories. When you pick up a new hobby, try a recipe a friend recommended, or read the latest world news, your brain stores many of these memories for years or decades. But how does your brain achieve this incredible feat? In our newly published research in the journal Science, we have identified some of the rules the brain uses to learn. Learning in the brain The human brain is made up of billions of nerve cells. These neurons conduct electrical pulses that carry information, much like how computers use binary code to carry data. These electrical pulses are communicated with other neurons through connections between them called synapses. Individual neurons have branching extensions known as dendrites that can receive thousands of electrical inputs from other cells. Dendrites transmit these inputs to the main body of the neuron, where it then integrates all these signals to generate its own electrical pulses. It is the collective activity of these electrical pulses across specific groups of neurons that form the representations of different information and experiences within the brain. For decades, neuroscientists have thought that the brain learns by changing how neurons are connected to one another. As new information and experiences alter how neurons communicate with each other and change their collective activity patterns, some synaptic connections are made stronger while others are made weaker. This process of synaptic plasticity is what produces representations of new information and experiences within your brain. In order for your brain to produce the correct representations during learning, however, the right synaptic connections must undergo the right changes at the right time. The rules that your brain uses to select which synapses to change during learningwhat neuroscientists call the credit assignment problemhave remained largely unclear. Defining the rules We decided to monitor the activity of individual synaptic connections within the brain during learning to see whether we could identify activity patterns that determine which connections would get stronger or weaker. To do this, we genetically encoded biosensors in the neurons of mice that would light up in response to synaptic and neural activity. We monitored this activity in real time as the mice learned a task that involved pressing a lever to a certain position after a sound cue in order to receive water. We were surprised to find that the synapses on a neuron dont all follow the same rule. For example, scientists have often thought that neurons follow what are called Hebbian rules, where neurons that consistently fire together, wire together. Instead, we saw that synapses on different locations of dendrites of the same neuron followed different rules to determine whether connections got stronger or weaker. Some synapses adhered to the traditional Hebbian rule where neurons that consistently fire together strengthen their connections. Other synapses did something different and completely independent of the neurons activity. Our findings suggest that neurons, by simultaneously using two different sets of rules for learning across different groups of synapses, rather than a single uniform rule, can more precisely tune the different types of inputs they receive to appropriately represent new information in the brain. In other words, by following different rules in the process of learning, neurons can multitask and perform multiple functions in parallel. Future applications This discovery provides a clearer understanding of how the connections between neurons change during learning. Given that most brain disorders, including degenerative and psychiatric conditions, involve some form of malfunctioning synapses, this has potentially important implications for human health and society. For example, depression may develop from an excessive weakening of the synaptic connections within certain areas of the brain that make it harder to experience pleasure. By understanding how synaptic plasticity normally operates, scientists may be able to better understand what goes wrong in depression and then develop therapies to more effectively treat it. These findings may also have implications for artificial intelligence. The artificial neural networks underlying AI have largely been inspired by how the brain works. However, the learning rules researchers use to update the connections within the networks and train the models are usually uniform and also not biologically plausible. Our research may provide insights into how to develop more biologically realistic AI models that are more efficient, have better performance, or both. There is still a long way to go before we can use this information to develop new therapies for human brain disorders. While we found that synaptic connections on different groups of dendrites use different learning rules, we dont know exactly why or how. In addition, while the ability of neurons to simultaneously use multiple learning methods increases their capacity to encode information, what other properties this may give them isnt yet clear. Future research will hopefully answer these questions and further our understanding of how the brain learns. William Wright is a postdoctoral scholar in neurobiology at the University of California, San Diego. Takaki Komiyama is a professor of neurobiology at the University of California, San Diego. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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E-Commerce
Just a few months into Donald Trumps second term, are the manosphere influencers who championed him already starting to backpedal? In a recent episode of The Joe Rogan Experience, host Joe Rogan raised concerns about the presidents decision to send undocumented immigrants directly to El Salvadors mega-prisonswithout trial, lawyers, or, as critics argue, any semblance of due process. “What if you are an enemy of, lets not say any current president. Lets pretend we got a new president, totally new guy in 2028, and this is a common practice now of just rounding up gang members with no due process and shipping them to El Salvador, youre a gang member. No, Im not. Prove it. What? I got to go to court. No. No due process,” said Rogan. We gotta be careful we dont become monsters, while fighting monsters. For those who had been sounding the alarm during Trumps campaign, it was a painful watch. Watching Joe Rogan figure this shit out in real time is painful, one commenter wrote. That ol Even a broken clock is right twice a day idiom comes to mind, another added. As one Reddit comment pointed out, Why does he need to use a hypothetical president to make this point? This entire commentary describes the current administration. View this post on Instagram A post shared by The Tennessee Holler (@thetnholler) This election cycle, Trump owes at least part of his victory to Rogan and other manosphere influencers who endorsed him. After hosting the now-president on The Joe Rogan Experiencein what became one of the most-watched podcast episodes of all time, with 58 million views at the time of writingRogan followed up with a full-throated endorsement just one day before the 2024 election. Are we now seeing the first cracks appear? Rogan isnt the only vocal Trump supporter expressing unease in recent weeks. Barstool Sports founder Dave Portnoy, who publicly backed Trump during the campaign, voiced frustration after the presidents rollout of sweeping tariffs sent markets into a nosedive. Portnoy claimed he lost $7 million in the aftermath. So, Trump rolls out the tariffs, right? Portnoy said in a livestream posted April 7. This is a decision that one guy made that crashed the whole stock market. Thats why were calling it Orange Monday and not Black Monday. Just days earlier, Portnoy had reaffirmed his support for Trump. I voted for Trump, I think hes a smart guy, he said in a clip. I also think hes playing a high-stakes game here. Im gonna roll with him for a couple days, a couple weeks, see how this pans out. By Monday, he said his estimated losses had climbed to $20 million.
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The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. Theres no question that artificial intelligence has taken the world by storm. However, as the initial excitement over the technology fades, we find ourselves in a new phase of thoughtful exploration. There are many innovative AI startups that have captured the worlds attention; however, many organizations still struggle to develop a clear roadmap to take full advantage of this transformative technology. So, whats the hold up? And how can business leaders avoid fleeting trends, effectively align their teams, and successfully integrate AI to achieve measurable impact and ROI for their business? Embrace the journey AI is already transforming industries, boosting efficiency and automating tasks ranging from data entry and language translation to document processing. And the benefits are clearrecent Accenture research found that the vast majority of organizations are seeing stronger-than-expected returns from their generative AI investments. Still, its important to keep a balanced perspective. While many AI solutions promise substantial benefits, the real challenge is identifying those that add tangible value. With new technologies emerging almost weekly, some leaders may also hesitate to invest because they are unsure if a better option is just around the corner. AIs true power comes from practical, enterprise-ready applications. For business leaders wondering where to start, the key is identifying the right challenges to tackle and knowing when and how to implement solutions effectively. Here are seven actionable tips to help you navigate this exciting landscape and build an AI decision-making framework tailored to your organizations needs. 1. Identify the use case First, pinpoint your specific needs and business objectives. Start within your organization, identifying pain points AI can address. Think about what AI does well, like spotting patterns, crunching numbers, and making predictions. Could it help with document translation, content creation, or customer insights? With so many potential applications, determining where to start might seem daunting. A focused, purposeful approach ensures youre investing in AI solutions that deliver real results. 2. Consider specialized models Over the last two years, we’ve seen much of the excitement around general purpose AI models outpace their value. As you evaluate AI tools for your organization, consider specialized AI models offering tailored solutions for specific industry needs. General AI models can do many things pretty well, but for higher stakes and more specific demands, specialized models often address complex, industry-specific challenges more effectively. For example, healthcare AI models can help doctors identify diseases more accurately, while banks use credit-scoring AI to determine whos likely to pay back loans. Language AI tools like DeepL are also specialized to businesses communicating across languages and markets. Specialized AI offerings are trained on domain-specific data optimized for particular tasks or industries, delivering enhanced quality and accuracy with lower risk of errors. Theyre also often designed with built-in compliance features aligned with industry regulations. This makes them more cost-effective, with clearer ROI. 3. Are humans the answer? When youre holding a hammer, everything looks like a nail, right? As the founder of an AI company, you might be surprised to hear me say this, but just because AI is the big thing right now doesnt mean its the singular solution for every problem or opportunity. So before diving into the deep end, consider if a human solution might actually be more effective than AI. Weighing what people, supported by AI, do best versus what AI can offer on its own, will help ensure you take the right approach for your organization’s needs. 4. Start with pilot projects If youre about to deploy an AI solution for the first time, begin with pilot projects to test your AI integrations in smaller, controlled environments. Starting small with a more limited investment reduces overall risk and can allow you to gather real-world data, monitor performance, and assess alignment with business goals before scaling. Pilot projects can also help build confidence within your teams and among leadership, making way for more successful full-scale AI deployments. 5. Invest in tech (and training) To truly harness AI’s potential, focus on bringing in new talent and continuously training existing employees. Depending on the implementations complexity, you might need new positions like data scientists, machine learning engineers or specialists. Upskilling your existing workforce can be equally essential to ensure employees can adapt and thrive alongside technological advancements. 6. Have a solid data strategy in place AI requires large volumes of data to perform its best, so it’s essential to have a solid data strategy infrastructure in place. Your plan should address how your organization will collect, securely store and access data; ensure compliance with evolving data privacy regulations, copyright standards and ethical guidelines; and assign responsibility for ongoing data governance and management. Answering these questions up front will save your company stress and problems later. 7. Refresh your ROI framework and adjust it regularly Most business leaders can recall digital initiatives that didn’t meet expectations, which can lead to concerns that their AI investments might follow a similar path. To enhance your ROI, outline your initiatives measurable goals, such as efficiency, cost savings, or an enhanced customer experience. Establish baseline metrics to understand current performance; then track improvements directly linked to AI. Its important to be adaptable, regularly revisiting goals and metrics to reflect evolving business priorities, market conditions, and technological changes. Unlike standard digital projects, AI initiatives can uncover new opportunities or shift mid-course. Also consider AI’s long-term strategic advantages, which may take time to come to fruition. From hyperbole to high performance To make AI work, organizations should shift their focus from what’s trending to enterprise-ready solutions that deliver lasting and specific value. Define your use cases up front, adopt an agile ROI framework, a robust data strategy, and commit to continuous improvement. This will unlock AI’s transformative potential and build a foundation for long-term competitive advantage. Jarek Kutylowski is CEO and founder of DeepL.
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E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. Across industries, a new era of climate innovation is accelerating. The momentum is visible in the data: Global clean energy investment surpassed $2 trillion for the first time in 2024, double the amount invested in fossil fuels. While solar panels, wind turbines, and grid-connected batteries often grab the headlines, the low carbon economy is growing in far more corners than many realize. Since founding Supercool last summer to cover proven and scaling climate solutions, Ive seen needle-moving innovation accelerating across farms, factories, and finance departments. One sector in particular shows remarkable progressthe built environment, which accounts for 34% of global carbon emissions. From hard tech and material breakthroughs to AI-powered intelligence to novel business models, here are three approaches to decarbonizing buildings happening now. 1. Hardtech innovation: Build with carbon-negative materials The engineered materials we use to build our suburbs and citiesprimarily timber, concrete, and steelcreate a lot of carbon emissions in their manufacture. Concrete and steel account for nearly 18% of global greenhouse gas emissions. Wood-based materials like oriented strand board (OSB), which are commonly installed in new homes, generate most of their manufacturing carbon emissions from burning wood to generate heat during production. Plantd transforms the built environment using carbon-negative building materials derived from alternative biomassa hardy, fast-growing grass. Four years ago, I cofounded the company with two former SpaceX engineers. To realize its ambitions, Plantd established a new agricultural supply chain innovating at every step, from building an in-house tissue culture lab to establishing full-scale greenhouse operations to supplying commercial farmers with the companys proprietary grass. [Photo: Courtesy of Plantd] Why grass? Because it grows incredibly fast, like bamboo, rapidly removing atmospheric carbon in the process, and possesses the structural characteristics to be transformed into durable engineered building materials. Yet, the key to sequestering carbon in our materials is Plantds manufacturing technology. Our team pioneered a modular, electric-powered production line that turns grass into finished products that replace plywood and OSB in new home construction. Its a first-of-its-kind technology that distinguishes a Plantd production facility from every other engineered wood facility in the world; ours is the only one without a smoke stack on top of the building. This past fall, D.R. Horton, the largest homebuilder in America, which builds about one in every 10 U.S. homes, ordered 10 million Plantd panels, enough to form the walls and roofs of 90,000 new single-family homes. 2. Software innovation: Give buildings brains An even bigger source of building-related carbon emissions is the energy required to operate them. Globally, this accounts for 26% of all greenhouse gas emissions. The top culprit: HVAC systems. The heating, cooling, and ventilation equipment needed to keep us comfortable indoors are responsible for about 35% of all energy used in U.S. buildings. The challenge is that thermostats, even the smart ones, arent very bright. They can track whats already happened and react to whats happening right now, but they cannot anticipate changes in weather, occupancy, carbon intensity of the grid, and energy costs. BrainBox AI can. Using AI-powered intelligence, its cloud-based control system connects to the hundreds, sometimes thousands, of HVAC components in a building and sends them real-time instructions. The companys platform provides over 15,000 buildings worldwidefrom Nordstrom to Family Dollarwith the intelligence to see six hours into the future with 96% accuracy. By knowing the future, BrainBox AI cuts energy, costs, and carbon emissions and improves comfort. Its an easy-to-install solution that works with existing systems and equipment. The results? HVAC-related emissions reductions of up to 40% and energy savings as high as 25%. 3. Finance innovation: Make efficiency upgrades free Many buildings are stuck with legacy equipment that gets the job done but consumes far more energy than their more efficient modern counterparts. Yet, new equipment can cost hundreds of thousands of dollars, often placing upgrades out of reach. Budderfly has built one of the fastest-growing businesses in America by removing the cost barrier. The company identifies energy-intensive businesses like fast food chains and offers them a deal that sounds almost too good to be true: free upgrades to energy-efficient systems, including HVAC, lighting, refrigeration, and secrity. Budderfly foots the bills and shares the monthly energy savings with its customers. Scale is key to making this business model work. Budderfly has raised nearly $1 billion to pay for the equipment it installs in customer locations. Its rapid expansion enables it to secure preferential pricing from global equipment suppliers that individual owners and franchisees could never obtain independently. Budderfly also takes over billing, which is one less thing for customers to worry about, and gives the company a trove of data to drive further energy reductions and cost savings. From Taco Bell to McDonalds to Sonic, clients are guaranteed to see savings from day one. In 2024, Budderfly generated $200 million in revenue and now operates in more than 7,000 locations nationwide. Its customers collective energy use dropped 43% last year. The takeaway Whether its growing new materials, giving buildings the ability to think ahead, or reimagining who pays for energy systems, the low carbon economy isnt just coming someday. Its already being built. Josh Dorfman is the CEO and host of Supercool.
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E-Commerce
Tesla has reached a potentially lethal moment in its history, and it isn’t solely due to CEO Elon Musk’s political radicalization. Years of design and technology stagnation have led to a languishing model line and outdated technology. Back in 2023, I wrote that the beleaguered carmaker should aspire to survive and become yet another car manufacturer. Now that objective feels more pressingand distantthan ever. The company just announced a new quarter of abysmal vehicle sales. Teslas first quarter of 2025 was a disastera 71% decline in net income compared to the same quarter last yearexcept for a better-than-expected gross margin thanks to its energy business. Its EV sales cratered, with a 13% sales drop in relation to the previous quarter. Worse yet: The company would have posted a loss if it werent for the government’s zero-emission credits. Predictably, Musk tried to distract from all of this with more of his usual empty promises about self-driving cabs and magical robots. During the Q1 financials conference call, he declaredwith a faltering train of thoughtthat he remained optimistic about the future of the company. A future that is based on a large number of autonomous cars and autonomous humanoid robots. He said that he expects autonomy to start moving Teslas financial needle in mid-2026. Musk also claimed Teslas humanoid robot Optimus will be working at Teslas factories by years end. I feel confident we will make a million units per year in less than five years, maybe four years, he said. Tesla will be the most valuable company in the world by far if we execute well, he declared after a pause. Then he said it will be maybe as valuable as the next five companies combined. Delay tactics Is anyone falling for all this bluster? Im not. You shouldnt either. Musks promises have a tendency to end in the graveyard of delusions, some of them literally buried, most delayed for many years. During the Cybercab reveal in October 2024, he promised the two-seater with scissor doors and no steering wheel by 2026, a claim that was met with derision. Remember that he promised robotaxis for 2020. The company declared in its Q1 report that the Cybercab is scheduled for volume production starting in 2026. Thats very unlikely to happen, as fully autonomous Tesla cars have not been approved anywhere, and they are far from going through the certification process needed for volume to happen. Waymo is still progressing slowly in its approval process and it’s years ahead of Tesla. Full Self-Driving manages just 489 miles between disengagements, dwarfed by Waymos 17,311, notes industry expert Ashok Elluswamy. To achieve human-level safety, analysts say, Tesla needs a 1,400x improvement. Which is why Musks claim of launching unsupervised Full Self-Driving (FSD) in June 2025 sounds so absurd. Teslas FSD currently remains a beta experiment linked to federal probes and crashes. Meanwhile, Volvo and Mercedes currently deploy safer autonomous tech made by Waymo, a company that already has self-driving cabs on the road. Even if Musk could actually deliver on his Cybercab promise, Teslas internal analysis admitted Robotaxis would hemorrhage cash. According to a report by The Information, the companys own executives warned Musk that the payback around FSD and Robotaxi would be slow . . . very, very hard outside the U.S. He ignored them. Instead, he canceled the Model 2the alleged name for an affordable Tesla modelto chase the geofenced 5mph Disneyland ride of Robotaxis, as critic Dan ODowd mocked. The company is now implicitly recognizing it made a mistake in its first quarter financial report, saying that more affordable options are as critical as ever. No wonder its top designers and engineers are leaving the company. Rotting design and cybertruck carnage During the call, Musk said he will focus more on Tesla and less on the government, blaming people benefiting from fraudulent government money for the protests against him. In his mind, these fraudsters are responsible for the company’s ongoing disaster, not him. But that shouldnt distract from the real reasons for the Teslapocalypse. This didnt happen because of Musk’s support for Donald Trump, though it did accelerate it. Even without Musks recent behavior, Tesla would still suffer from its preexisting condition and the bare facts of its business model: stale design, no forward vision, no technolgical innovation. This is a trifecta for failure. Tesla lacks what it needs to save itself from the current realities of the automobile market. Chinamainly BYD and brands like Xiaomi and Xpenghas established itself as the clear design and technological car manufacturing leader in the world, resulting in its top spot in global sales, despite U.S. tariffs. And in Europe, Japan, and South Korea, the old brands have finally risen to the challenge, with BMWs EV sales in Europe overtaking Tesla for the first time in February of this year. Teslas collapse began with its rotting design DNA. The Model S is 10 years old now, Adrian Clarke, a veteran car designer, told me in 2023. Its other carsModels 3, X, and Ylook like spitting-image cousins. Its 2025, and except for a lackluster refresh of Model Y so unappealing that the company has just announced a zero-interest five-year buying plan, nothing has changed. Teslas lineup remains a museum of stagnation in an industry where everyone refreshes models yearly. Most manufacturers would replace a model after about seven or eight years, Clarke told me. But Tesla clings to a decade-old template, a strategy former Jaguar designer Jeremy Newman calls strategically irresponsible. How can anyone expect the market to keep buying Teslas when every other manufacturer is releasing new models, like BYDs Yangwang U7 and its magical suspension system that eliminates all bumps. Then theres the Xiaomi SU7 Ultra and its supercar features that come at regular sports car prices. Or the BMW iXthe best 2024 EV according to Consumer Reports. With this in mind, can anyone truly be surprised to see Teslas U.S. market share plummeting from 79.4% in 2020 to 65.4% in 2022 to 48.7% in 2024? Only the most deluded fanboys and Tesla bulls could ignore this. Everyone else is seeing the writing on the wall. The Cybertruck epitomizes Musks delusional leadership. When it launched, industry experts criticized and warned about its design. Cold, sterile, and almost repulsive, legendary designer Frank Stephenson spat. Everyone I know thought theres no way theyre gonna get that into production, Clarke said at the time. They were partially right. The trucks dead straight panels defied manufacturing logic, leading to countless recalls for razor-sharp frunks that slice fingers, accelerators that stick mid-drive, and bulletproof windows that can shatter from hail. By June 2024, more than 11,000 units faced recalls for failing wipers and loose trim. Sales cratered: After peaking at 16,692 units in Q3 2024, sales dropped to 12,991 in Q4a 22% decreaseand fell further to 6,406 in Q1 2025, marking a 50% decline from the previous quarter. Can it be saved? Now you can add cratering financials to this technological and design mayhem. Teslas Q4 2024 deliveries hit a record 495,570 vehicles, but the cost was catastrophic. Price cuts and 0% financing slashed profit margins, with average sales prices plunging to $41,000the lowest in four years. Annual deliveries fell 1.1% to 1.79 million, Teslas first decline since 2011. Meanwhile, BYD sold 595,413 battery electric vehicles in the same quarter. Analysts called Teslas performance an unmitigated disaster masked by temporary incentives. Today confirmed what we knew. Teslas first-quarter 2025 revenue came short of the estimated $21.1 billion at only $19.3 billion. Auto revenue fell 20%. Its the worst quarter in almost three years, and the companys first-ever year-to-year drop in sales. Sure, the protests at stores and vandalism of Tesla lots fueled by Musks polarizing politics didnt help this situation. But at the end of the day, if you give consumers the choice of buying a new EV design with superior technology at a lower price or a tired Tesla model, they will choose the former. Having a better product at the best price possible is the most important part for the long-term survival of any company. Talking to CNBC, Patrick George, editor-in-chief of InsideEVs, said the biggest operational challenge in the latest quarter was the nuts-and-bolts job of being a car company. For a car company that runs on, you know, car sales, things like robocabs and humanoid robots are a distraction. Its no wonder that Teslas stock plummeted since December. Meanwhile, the rest of the market keeps innovating at record speeds. BYDs flash-charging techrefueling EVs in five minutesand its Blade battery, hailed as the worlds safest, have left Tesla in the dust. The Xiaomi SU7, a luxury sports sedan priced like a Toyota, sold 88,898 units in 24 hours, proving Chinese brands can out-innovate and undercut. In Europe, BMW and Mercedes leveraged 60% customer loyalty to reclaim the luxury segment. People want cars that fit into their lives, Clarke told me two years ago. It was an industry lesson that Musk ignored. Legendary investor and economist Bruce Greenwald warned about all of this in 2021, way before Musk descended into the political mud: Twenty years from nowyou really think that [Tesla is] going to dominate the auto market? Not a chance. He was wrong by almost two decades. After todays results, there are only two questions in my mind. First: How much more value will Musk oblterate before shareholders eject him? And the other, more pressing question: Will the next CEO be able to save the company? Tesla needs to do something radical right now. And that should start with Musk leaving the company.
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E-Commerce
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