Tesla vehicles line a parking area at the company's factory in Fremont, California. Tesla vehicles line a parking area at the company's factory in Fremont, California. Carmaker exceeded Wall Street's expectations with more than $26bn in revenue, but saw a 37% drop in profits Despite record vehicle sales, Tesla saw a precipitous drop in profit in its most recent quarter. A rush to buy electric vehicles before a US tax credit for them disappears had boosted Tesla's flagging sales, leading to the automaker exceeding some of Wall Street's projections in its most recent financial quarter. Yet the company failed to meet earnings expectations and its stock fell in after-hours trading.

The electric vehicle tax credit is gone, and Tesla's new, more affordable models don't quite close the gap. For nearly two decades, CEO Elon Musk has promised Tesla would make a more affordable electric vehicle, to, as he put it in 2006, "help expedite the move from a mine-and-burn hydrocarbon economy towards a solar electric economy." On Tuesday, Tesla announced a new Model Y and Model 3 Standard, versions of its popular compact SUV and sedan stripped of a few higher-end touches and features to bring the price down to $39,990 and $36,990, respectively. They're both about $5,000 cheaper than the Premium variants, which goes a ways--but not all the way--toward recouping the $7,500 tax credit canceled by the GOP-led Congress this past summer . The price point also puts Tesla's newest models firmly in the "more affordable" EV camp.

EV tax credits are dead in the US. Federal EV tax credits in the US officially came to an end yesterday. Those credits, expanded and extended in the 2022 Inflation Reduction Act, gave drivers up to $7,500 toward the purchase of a new electric vehicle. They've been a major force in cutting the up-front costs of EVs, pushing more people toward purchasing them and giving automakers confidence that demand would be strong. The tax credits' demise comes at a time when battery-electric vehicles still make up a small percentage of new vehicle sales in the country. This article is from The Spark, MIT Technology Review's weekly climate newsletter.

Can AI file your taxes? Not yet. Calculating US personal income taxes is a task that requires building an understanding of vast amounts of English text and using that knowledge to carefully compute results. We propose TaxCalcBench, a benchmark for determining models' abilities to calculate personal income tax returns given all of the necessary information. Our experiment shows that state-of-the-art models succeed in calculating less than a third of federal income tax returns even on this simplified sample set. Our analysis concludes that models consistently misuse tax tables, make errors in tax calculation, and incorrectly determine eligibility. Our findings point to the need for additional infrastructure to apply LLMs to the personal income tax calculation task.

After more than a day of continuous debate, the US Senate passed its version of the budget megabill Tuesday afternoon--with potentially disastrous implications for the future of renewable energy in the country. The bill ends credits for projects placed in service--a term meaning, essentially, that a project is ready to provide power to the grid--after 2027, putting hundreds of planned projects around the country in jeopardy. "This is a bill to punish renewables," says Costa Samaras, a professor of civil and environmental engineering at Carnegie Mellon University. "There is a real need to add clean energy supply to the grid--electrifying our cars, electrifying our homes, electrifying our buildings, electrifying our factories, and the demands from AI are all going to require new clean energy. What this bill does is make it harder and more expensive."

It only took a few hours to wipe 152 billion of value from Tesla's market cap and more than 100 million in value from TrumpCoin. The end of the bromance between Elon Musk and President Donald Trump has been brewing for weeks, but on Thursday, the breakup went nuclear. Musk took to the platform he owns, X, to lambast Trump's "One Big Beautiful Bill," which includes provisions that restrict immigration, limit green energy subsidies, and is estimated to increase the US deficit by 2.4 trillion. Trump shot back on Truth Social, the platform he owns, to say that Musk was only against the bill because it would take away electric vehicle tax credits that Musk's company, Tesla, benefits from. It quickly devolved into dozens of posts, most of them from Musk, who claimed Trump is in the Epstein Files--which is, he claims, why they haven't been made public. Tesla's stock is now down roughly 14 percent at the time of writing, which is the biggest single-day hit to its market cap in years.

On Wednesday, during a gathering at Mar-a-Lago attended by some of Donald Trump's closest associates, a speaker demanded, "Where is the George Soros of the right?" In a scene that an attendee captured on video, Elon Musk, the fifty-three-year-old South African-born billionaire who reportedly spent about a hundred and thirty million dollars to aid Trump's campaign and support other Republicans in competitive races, raised his arm. Amid loud cheers, the speaker declared, "God bless you, Elon. We are so, so grateful." Musk has claimed publicly that he has never asked Trump for any favors, and that Trump has not offered him any. Despite spreading misinformation on X, his social-media platform, and heavily financing the campaign of someone who plotted an autogolpe, he has also denied being a political extremist.

To understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular design, (ii) multiple transportation modes, (iii) capabilities for extension, and (iv) testing against various system components and networks of small and large sizes. Five matching algorithms for CO2 supply agents (e.g., powerplants and industrial facilities) and demand agents (e.g., storage and utilization sites) are explored: Most Profitable First Year (MPFY), Most Profitable All Years (MPAY), Shortest Total Distance First Year (SDFY), Shortest Total Distance All Years (SDAY), and Shortest distance to long-haul transport All Years (ACAY). Before matching, the supply agent, demand agent, and route must be available, and the connection must be profitable. A profitable connection means the supply agent portion of revenue from the 45Q tax credit must cover the supply agent costs and all transportation costs, while the demand agent revenue portion must cover all demand agent costs. A case study employing over 5,500 supply and demand agents and multimodal CCUS transportation infrastructure in the contiguous United States is conducted. The results suggest that it is possible to capture over 9 billion tonnes (GT) of CO2 from 2025 to 2043, which will increase significantly to 22 GT if the capture costs are reduced by 40%. The MPFY and SDFY algorithms capture more CO2 earlier in the time horizon, while the MPAY and SDAY algorithms capture more later in the time horizon.

There has been a growing interest in multi-agent simulators in the domain of economic modeling. However, contemporary research often involves developing reinforcement learning (RL) based models that focus solely on a single type of agents, such as households, firms, or the government. Such an approach overlooks the adaptation of interacting agents thereby failing to capture the complexity of real-world economic systems. In this work, we consider a multi-agent simulator comprised of RL agents of numerous types, including heterogeneous households, firm, central bank and government. In particular, we focus on the crucial role of the government in distributing tax credits to households. We conduct two broad categories of comprehensive experiments dealing with the impact of tax credits on 1) households with varied degrees of myopia (short-sightedness in spending and saving decisions), and 2) households with diverse liquidity profiles. The first category of experiments examines the impact of the frequency of tax credits (e.g. annual vs quarterly) on consumption patterns of myopic households. The second category of experiments focuses on the impact of varying tax credit distribution strategies on households with differing liquidities. We validate our simulation model by reproducing trends observed in real households upon receipt of unforeseen, uniform tax credits, as documented in a JPMorgan Chase report. Based on the results of the latter, we propose an innovative tax credit distribution strategy for the government to reduce inequality among households. We demonstrate the efficacy of this strategy in improving social welfare in our simulation results.

New Jersey has a new plan to become the US hub for AI innovation. The state's governor signed a law on Thursday that will offer up to 500 million in tax credits for artificial intelligence companies to set up shop in the state. "We want New Jerseyans to stand at the forefront of the AI revolution--and build a more prosperous world in the process," New Jersey's Governor, Phil Murphy, a Democrat, said in a statement. "And in so doing, we are going to establish New Jersey as the home-base for R&D in generative AI." AI companies and data centers that power AI that operate at large scales in New Jersey can qualify for the tax credits, which divert unspent funds from two other state tax credit programs for job creation and real estate development enacted in response to the Covid-19 pandemic. Critics of the plan fear that it could be a win for profitable AI companies, but a loss for the state.