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Its summer, and its been hot, even in northern cities such as Boston. But not everyone is hit with the heat in the same way, even within the same neighborhood. Take two streets in Boston at 4:30 p.m. on a recent day, as an example. Standing in the sun on Lewis Place, the temperature was 94 degrees Fahrenheit (34.6 degrees Celsius). On Dudley Common, it was 103 F. Both streets were hot, but the temperature on one was much more dangerous for peoples health and well-being. The kicker is that those two streets are only a few blocks apart. The difference epitomizes the urban heat island effect, created as pavement and buildings absorb and trap heat, making some parts of the city hotter. A closer look at the two streets shows some key differences: Dudley Common is public open space sandwiched between two thoroughfares that create a wide expanse of pavement lined with storefronts. There arent many trees to be found. Lewis Place is a residential cul-de-sac with two-story homes accompanied by lots of trees. This comparison of two places within a few minutes walk of each other puts the urban heat island effect under a microscope. It also shows the limits of todays strategies for managing and responding to heat and its effects on public health, which are generally attuned to neighborhood or citywide conditions. Even within the same neighborhood, some places are much hotter than others owing to their design and infrastructure. You could think of these as urban heat islets in the broader landscape of a community. Sensing urban heat islets Emerging technologies are making it easier to find urban heat islets, opening the door to new strategies for improving health in our communities. While the idea of reducing heat across an entire city or neighborhood is daunting, targeting specific blocks that need assistance the most can be faster and a much more efficient use of resources. Doing that starts with making urban heat islets visible. In Boston, Im part of a team that has installed more than three dozen sensors across the Roxbury neighborhood to measure temperature every minute for a better picture of the communitys heat risks, and were in the process of installing 25 more. The Common SENSES project is a collaboration of community-based organizations, including the Dudley Street Neighborhood Initiative and Project Right Inc.; university researchers like me who are affiliated with Northeastern Universitys Boston Area Research Initiative; and Boston city officials. It was created to pursue data-driven, community-led solutions for improving the local environment. Data from those sensors generate a real-time map of the conditions in the neighborhood, from urban heat islets like Dudley Common to cooler urban oases, such as Lewis Place. These technologies are becoming increasingly affordable and are being deployed in communities around the world to pinpoint heat risks, including Miami, Baltimore, Singapore, and Barcelona. There are also alternatives when long-term installations prove too expensive, such as the U.S.s National Oceanic and Atmospheric Administration volunteer science campaign, which has used mobile sensors to generate onetime heat maps for more than 50 cities. Making cooler communities, block by block Although detailed knowledge of urban heat islets is becoming more available, we have barely scratched the surface of how they can be used to enhance peoples health and well-being. The sources of urban heat islets are rooted in developmentmore buildings, more pavement, and fewer trees result in hotter spaces. Many projects using community-based sensors aspire to use the data to counteract these effects by identifying places where it would be most helpful to plant trees for shade or install cool roofs or cool pavement that reflect the heat. However, these current efforts do not fully capitalize on the precision of sensors. For example, Los Angeless massive investment in cool pavement has focused on the city broadly rather than overheated neighborhoods. New York Citys tree planting efforts in some areas failed to anticipate where trees could be successfully planted. Most other efforts compare neighborhood to neighborhood, as if every street within a neighborhood experiences the same temperature. London, for example, uses satellite data to locate heat islands, but the resolution isnt precise enough to see differences block by block. In contrast, data pinpointing the highest-risk areas enables urban planners to strategically place small pocket parks, cool roofs, and street trees to help cool the hottest spaces. Cities could incentivize or require developers to incorporate greenery into their plans to mitigate existing urban heat islets or prevent new ones. These targeted interventions are cost-effective and have the greatest potential to help the most people. But this could go further by using the data to create more sophisticated alert systems. For example, the National Weather Services Boston office released a heat advisory for July 25, 2025, the day I measured the heat in Dudley Common and Lewis Place, but the advisory showed nearly the entirety of the state of Massachusetts at the same warning level. What if warnings were more locally precise? On certain days, some streets cross a crucial thresholdsay, 90 Fwhereas others do not. Sensor data capturing these hyperlocal variations could be communicated directly to residents or through local organizations. Advisories could share maps of the hottest streets r suggest cool paths through neighborhoods. There is increasing evidence of urban heat islets in many urban communities and even suburban ones. With data showing these hyperlocal risks, policymakers and project coordinators can collaborate with communities to help address areas that many community members know from experience tend to be much hotter than surrounding areas in summer. As one of my colleagues, Nicole Flynt of Project Right Inc., likes to say, Data + Stories = Truth. If communities act upon both the temperature data and the stories their residents share, they can help their residents keep coolbecause its hot out there. Dan O’Brien is a professor of public policy and urban affairs and director of the Boston Area Research Initiative at Northeastern University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Each January, we set lofty resolutions for ourselves: increasing our output, landing that promotion, and negotiating a raise. Then progress stalls, motivation dips, and those big goals become distant dreams. Research from Headwaya book summary app designed to help people achieve their self-development goalsshows that 60% of people are embarrassed by how little progress theyve made this year, with 44% close to writing off their 2025 resolutions. As a productivity coach, I know how beneficial resolutions can bebut also how quickly they can sap morale and motivation when combined with the wrong mindset. But it doesnt have to be all or nothing. Theres no deadline, and you havent failed if you dont complete your resolutions by December 31st. So if youve hit a midyear slump, dont panic. These strategies can help you to reset, refocus, and rebuild momentum: 1. Reframe your setbacks Setback carries negative connotations, but its just another word for experience, and experience is essential for growth. Instead of brushing these moments asideor beating yourself up over themnote down each time youve tried and failed, then reflect on what these experiences taught you, shifting your mindset from self-criticism to self-awareness. Where did it go wrong, and what would you do differently next time? Setbacks arent roadblocks; theyre stepping stoneswith each one providing valuable insight that will aid your next attempt, making you more resilient and better prepared. In fact, research shows that a failure rate of around 15% is optimal for self-growth. 2. Utilize the Zeigarnik effect Many people recommend breaking your resolutions down into smaller, more achievable tasks. Yet, that constant sense of achievement can kill your productivity. You tick a small step off your to-do list and reward yourself with a break, hitting reset on your momentum. Instead, you need to use the Zeigarnik effect to your advantage. This is a phenomenon where our brains are hardwired to focus on unfinished tasks and quickly forget about the ones weve completed. Instead of wrapping up your day with your to-do list at 100% completed, end at 80%. The next day, youll be ready to pick up where you left off. But once you finish a task, move immediately on to the next to keep the momentum going. This approach will keep your goal front of mind, maintain a sense of urgency, and prevent that post-completion slump that too often derails our progress. 3. Cut yourself some slack Youre not the person you were six months ago. Life shifts and priorities change, so your January goals might be unrealistic today. Thats okay. Some 27% of people say simply surviving 2025 is commendableand theyre right. Close to half fear a global conflict is on the horizon, one in five find themselves worrying that a loved one could face deportation, and there has been a sharp rise in the number of people struggling to make ends meet. Tensions are high, and were all struggling with something, so go easy on yourself. If you need to scale back your resolutions or hit pause until 2026? Theres no shame in it. 4. Stop striving for perfection You dont have to navigate your goals aloneor stick rigidly to the resolutions you set in January. You simply need to stay connected to your intentions, especially when motivation starts to dip. That might mean scheduling regular check-ins with yourself where you can remind yourself why you set certain goals in the first place, take time to note whats working and what isnt, and adjust accordingly to match the current pace of life. Progress isnt about perfection. Its about staying in tune with what matters most to you and seeking to better yourself. By being too tough on yourselfdenying yourself the space, flexibility, and self-trust to get there in the endyoure not pushing yourself to achieve; youre pushing yourself to quit. 5. Focus on recovery With 61% of people having suffered a meltdown in 2025, its clear were demanding too much of ourselves, and another midyear resolution wont help. The problem is, we set ambitious goals on top of our already overloaded schedules, then sacrifice our sleep and downtime to pursue them. Its no surprise we burn out when our bodies and minds are running on empty. So instead of pushing yourself to do more, push yourself to rest more. Your midyear resolutions should be to sleep eight hours each night, stop checking your emails after hours, and use up all your vacation days. Theres a reason athletes take rest days and CEOs swear by meditation. Whats good for the body and mind is great for productivity, so if you set resolutions that help you rest, relax, and recover, your career will undoubtedly profit.
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It’s not uncommon for large companies to acquire startups primarily for their talent rather than their product. Acquihires, as they are called, allow big companies to gain talented employees, while bypassing traditional methods of hiring. However, as the AI talent wars have heated up, major companies like Meta, Google, and Microsoft have been engaging in reverse-acquihires at AI startups. That is, they are swooping in to hire star talent and license technology, discarding the rest by the wayside. The tech giants gain talent while sidestepping the need for government approval and antitrust scrutiny that would happen if they bought the company outright. The remaining employees are left to flounder in the husk of their former company. By Bloombergs count there have been six since last March, and as the AI talent wars continue, were likely to see more. 6. Google DeepMind and Windsurf In July 2025, Googles DeepMind division hired Windsurf CEO Varun Mohan and cofounder Douglas Chen, along with other key members of their R&D team. The $2.4 billion deal also included Windsurf technology. Google did not take a stake or any controlling interest in the startup. The deal came after Windsurf was nearly sold to OpenAI in what was set to be a $3 billion deal. The Windsurf employees whom Google did not hire went from expecting to be part of OpenAI to being left behind at a company with no leaders. In a surprise twist Windsurf was quickly acquired by AI coding startup, Cognition. Still, the story doesnt have a happy ending. Shortly afterwards, Cognition laid off 30 members of Windsurfs team and offered buyouts to the remaining 200 TechCrunch reported. 5. Meta and Scale AI This June, Meta finalized a deal with data labeling company Scale AI. Meta acquired a group of its top engineers, including founder Alexandr Wang, and took a 49% stake in the company, for a $15 billion price tag. “As part of this, we will deepen the work we do together producing data for AI models and Alexandr Wang will join Meta to work on our superintelligence efforts,” a Meta spokesperson said. A month later, Scale laid off 14% of its workforce. Interim CEO Jason Droege said the company plans to focus on its government and enterprise businesses going forward. 4. Google and Character.AI In August 2024, Google also struck a deal with chatbot startup Character.AI, hiring its founders Noam Shazeer and Daniel De Freitas, as part of a $2.7 billion deal. “Were excited to announce that weve entered into an agreement with Google that will allow us to accelerate our progress,” Character.AI said in a statement at the time. The statement also explained that the startup would grant a nonexclusive license to the tech giant for its LLM technology. In the wake of the reverse-acquihire, Character.AI has shifted to a cheaper business model. Instead of training LLMs, it simply develops AI characters. Interim CEO Dominic Perella told Bloomberg: We were left much better positioned than some folks, pointing out that for a reverse-acquihire Character.AI is doing well. 3. Amazon and Covariant In August 2024, Amazon hired robotics company Covariants three founders (Peter Chen, Pieter Abbeel, and Rocky Duan) as well as about a quarter of the staff. They also received a nonexclusive license to Covariants robotic foundation models. According to a whistleblower, Amazon paid $380 million, which is much higher than $119.5 million, which is when deals need to be reported to the FTC. The Washington Post reported that according to the whistleblowers filing, Covariants current CEO, Ted Stinson, said if Amazon had bought the company outright, the deal would have been killed by antitrust authorities. According to the whistleblower, the deal restricts which licenses Covariant can sell without paying a fee to Amazon, hobbling its ability to grow. The whistleblowers filing said Covariant was only expected to last for a year after the deal went through. 2. Amazon and Adept Similarly, in June 2024, Amazon hired CEO David Luan and most of the AI startup Adept’s 100-person team in a deal that also included licensing the startup’s technology. At the time, Adept, which had raised $400 million, was developing AI agents to do software tasks, and the deal came before it had launched a product. Post-deal a blog post from Adept seemed to suggest that the company was now low in fund and needed to shift to a cheaper business model. Continuing with Adepts initial plan of building both useful general intelligence and an enterprise agent product wouldve required spending significant attention on fundraising… the post stated. Adept will now focus entirely on solutions that enable agentic AI, which will continue to be powered by a combination of our existing state-of-the-art in-house models, agentic data, web interaction software, and custom infrastructure. In December 2024, Amazon announced it was launching a new lab led by David Luan that would build AI agents that can handle complex workflows. Only around 20 employees remained at Adept after the Amazon deal. Bloomberg noted only four people currently list Adept as their employer on LinkedIn. 1. Microsoft and Inflection Microsoft kicked off the reverse acquihire trend last March when it agreed to pay chatbot startup Inflection about $653 million in a deal that effectively gutted the startup. The move included hiring founders Mustafa Suleyman and Karén Simonya and most of Inflection’s staff. Around $620 million was for nonexclusive licensing rihts to Inflection’s AI models, and a $33 million payment for Inflection to waive any legal claims related to the hiring of its staff. Inflection had raised $1.3 billion in June 2023. However, Bloomberg noted CEO Suleyman was worried about the companys ability to raise enough funds to stay viable given the size of its competition. The deal triggered a FTC investigation to determine whether it was designed to avoid antitrust review while allowing Microsoft control over Inflection. Inflection is still in operation, but has changed course to focus from building new AI models to working on AI in the enterprise space. Sean White, a former Mozilla executive, became the new CEO. White told Bloomberg that Inflection is still in rebuilding mode: The ship, over time, was slowly replaced, board by board, piece by piece, right? But it was still always the same ship, he said.
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