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Want more housing market stories from Lance Lamberts ResiClub in your inbox? Subscribe to the ResiClub newsletter. Back on January 7, President Donald Trump announced: I am immediately taking steps to ban large institutional investors from buying more single-family homes, and I will be calling on Congress to codify it. On January 20, Trump went further, outlining elements of the proposed ban. The order directed multiple federal agenciesincluding HUD, the Department of Agriculture, the VA, the GSA, and the Federal Housing Finance Agencyto issue guidance within 60 days limiting the federal governments role in facilitating institutional purchases of single-family homes that could otherwise be bought by owner-occupants. Specifically, within 60 days, the government-sponsored enterprises (Fannie Mae and Freddie Mac) would no longer be permitted to approve, insure, guarantee, or securitize single-family home purchases by large institutional investors. The order also stated that, within 30 days, the administration would define large institutional investors and that build-to-rent transactions would be exempt. On Thursday (February 19), the Wall Street Journal reported that the White House has settled on a key detail of its proposed banone it plans to send to Congressprohibiting large investors, defined as entities owning 100 or more homes, from purchasing additional single-family houses. Because the threshold is set at 100 homes, the policy would affect not just major institutional landlords, but also some larger individual investors. The plan still includes the build-to-rent exemption and adds another carveout: large investors can continue to purchase homes in need of significant repair. Those two proposed exemptions are notable given that most institutional activity right now is in build-to-rent, and when purchasing scattered-site homes, institutional investorsat least when they are actively buyingtend to target properties that require sizable renovation spending. Notably, this proposal would not mandate large investors to liquidate existing holdings. The measure announced on Thursday would need congressional approval, and its prospects are uncertain. According to reporting from the Wall Street Journal, passage is still far from guaranteed. At the height of the Pandemic Housing Boom, large investorsthose owning at least 100 single-family homesmade up an all-time high of 3.1% of home purchases in Q2 2022, according to John Burns Research and Consulting. That period, at the tail end of the boom, was when yields were particularly attractive as borrowing costs were ultra-low, home prices were soaring, and rents were climbing rapidly. However, since mortgage rates spiked and capital markets shifted, their share has fallen to around 1.0% of transactions over the past three years. The math isnt as favorable right now. ResiClub members (paid tiers) can find an interactive version of the map below here On a national level, large investorsthose owning at least 100 single-family homesonly own around 1% of total single-family housing stock. That said, in a handful of regional housing markets, institutional and large single-family landlords have a much larger presence. Markets like Phoenix and Atlanta became major hubs for institutional single-family rental investment following the 2008 housing crash as the asset class started to institutionalize. Firms such as Invitation Homes, Progress Residential, and AMH built sizable portfolios in these metros by acquiring distressed homes. That early activity helped establish a reliable local SFR ecosystemincluding property management firms, leasing infrastructure, and contractor networksthat makes it easier to scale and expand single-family rental and build-to-rent operations today.
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A turf war has broken out between the fandoms of Breaking Bad and Game of Thrones over the highest-rated episode spot on IMDb. Released last month, the Game of Thrones spin-off A Knight of the Seven Kingdoms, set a century before the events of the HBO drama, has garnered much praise. A Guardian reviewer said it has “saved the Game of Thrones universe.” Fans appear to agree, as the fifth episode, In the Name of the Mother, which aired February 15, briefly secured a rare 10/10 rating on IMDb. Unfortunately for fans, it didnt last long. For over a decade, Ozymandiasthe 14th episode of the fifth and final season of Breaking Bad, and the climax of the serieshad been the only television episode to secure a perfect 10 rating on IMDb. Its an accolade fans werent prepared to give up lightly. Taking matters into their own hands, according to reports across Reddit and X, fans of the crime drama started review-bombing the A Knight of the Seven Kingdoms episode with one-star ratings to tank its score. The Ozymandias episode of BREAKING BAD has dropped to a 9.9 on IMDb.It held a 10/10 rating on the platform for almost 13 years. pic.twitter.com/9zLtW00a01— DiscussingFilm (@DiscussingFilm) February 20, 2026 One IMDb reviewer admitted as much, writing, I like this episode. I like this show overall. Hell, I love this episode. But… its not 1% as good as the episode mentioned in the title of this review is. I therefore decide the leave this one star review in order to defend the number one episode. What followed was an all-out review-bombing war between the two fandoms. On the IMDb review page for Ozymandias, a slew of reviews titled “The Lannisters Send Their Regards or Winter came for Breaking Bad! The North remembers started appearing. Meanwhile, of the hundreds of one-star reviews A Knight of the Seven Kingdoms has accumulated on IMDb so far, many hit back “in the name of walter white” or “For Heisenberg.” For the first time in 13 years, the Breaking Bad episode lost its perfect score on the site. At the time of writing, neither episode is in the top 10 list on the platformor even the top 100. A Knight of the Seven Kingdoms, now with an average score of 9.5, sits at number 519 on the best TV episode ranking. Ozymandias, now with an average score of 9.6, has dropped to number 461. The only winner here? Six Feet Under, which has now slipped into the top spot.
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AI is reshaping how work gets done in institutions, both public and private. However, the impact is unevenconsumer AI chat interfaces like ChatGPT, Copilot, Claude, and Gemini are fundamentally mismatched to the realities of government work. That doesnt mean government agencies arent turning to AI. They cannot hire their way to capacity, so theyre looking to technology to lighten the load. More than half of local governments report difficulty filling positions, a problem especially potent in larger metros. San Franciscos local government, for example, has more than 4,700 open positions. Since 2020, state government employment has increased, but much of that is a bounce-back from the pandemic, not true growth needed to deliver services with the efficacy governments want. But drop-in chatbots cant make a significant impact on operations because data within government agenciesand even within individual departments in agenciesis exceedingly siloed. State and local governments are managing budget constraints. IT teams are stretched thin. Its no surprise, then, that consumer AI tools dont meet their promise in government institutions. They fundamentally lack all the information they need to be effective in a public service context. THE TOOL GAP Commercial software tools, including AI chatbots, are built for private companies with hierarchies, contracts, and linear processes. Government work is inherently different. Public institutions are cross-organizational, the work is omnidirectional, and success necessitates constant collaboration across agencies, nonprofits, and community partners. Emergency management departments, for example, must identify points of contact within local police departments, fire departments, sheriffs offices, emergency medical services, utility companies, FEMA regional offices, and community emergency response teams to effectively deliver their servicecoordinating disaster response and recovery operations. The sum of these problemsfrom data siloes to budget constraints to technological roadblocksis that consumer AI struggles in government institutions because these tools lack the necessary context. Try asking ChatGPT Provide our current reimbursement process or Create a survey to gather feedback on the latest heat season coordination. These are tasks that require explicit, non-public knowledge. To execute such tasks, AI needs not only access to data that lives across disparate systems, but also governance and rules specifying which definition is best suited for each purpose. And even if you get a good answer, traditional AI is not built to help users know what to do next. THE PATH FORWARD Embedding AI is the path forward to deploy AI in government, effectively overcoming data silos to tackle inter-organizational work. Embeddedness refers to AI that lives directly within the platforms where work happens, within coordination, memory, and decision-making systemsnot inside a chatbot. Government is uniquely suited to benefit from AI thats truly embedded because it has the perfect raw material to make AI maximally useful: conversations, decisions, workflows, institutional memory, and loads of information. In other words, government has context. Unfortunately, most AI chatbots today assume their users work inside of a single organization, and therefore only need context from one organizations systems. For government, thats not the reality. A homelessness coordinator in Essex County or an election administrator in New York isn’t just working at one organization: they’re juggling relationships, meetings, decisions, and shared knowledge across constantly shifting agencies, nonprofits, contractors, and community partners. The hardest parts are aligning, coordinating, remembering, onboarding, and maintaining shared understanding across people who come and go. Because government work is inherently lateral, true embedded AI has information not only across one organizations systems but also across its partners systems, too. Taking the idea of embeddedness one step further, its vital for AI to seemingly disappear into public servants workflows. If AI is one more tool, one more thing government employees must be trained on, then AI is notembedded in the way it needs to be. Public servants dont want or need another new widget. They need technology that helps them do what they do faster, better, and more accurately. That is embedded AI. Consider this example: Its common for certain AI tools to send a summary and action items after a meeting. But embedded AI goes further. It would ask the user if they wanted a follow up email to socialize action items. It could draft the follow-up email, too. Then, after a couple of days, the embedded AI would surface engagement data, showing that someone assigned an action item hasnt read the follow-up email, and the AI would ask the user if they want a follow-up email, and then draft the note. When a public servant is searching for information, the next step is usually to read it to send something to somebody or take an action. AI that supports that next step without explicit prompting or forcing the user to switch tools is the kind of technology that can help public servants better deliver services more quickly. This is the shift that accelerates action. THE END GOAL Its vital we do not lose sight of the goal. State and local governments are where the rubber meets the road, turning rules into real servicesfrom handling daily operations to helping low-income people get nutrition assistance, providing veterans services, supporting people experiencing homelessness, and everything in between. Yes, chatbots and similar tools can help one person be more effective. But when AI is embedded, benefits are magnified; people and entire programs are faster and more effective. That means the people who rely upon municipal government services are better served. And that is the ultimate promise of technology, like embedded AI efficiently deployed in governmentbetter communities for all. Madeleine Smith is the CEO and cofounder of Civic Roundtable.
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