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Scientists genetically engineer houseplant to remove carcinogens from air
Scientists at the civil and environmental engineering department at the University of Washington have genetically modified a common houseplant to break down toxic molecules present in chlorinated water and gasoline. The plant, “pothos ivy”, was engineered to express a protein called 2E1 which enables the breakdown of benzene and chloroform into components the plant can use for its own needs. The targeted chemicals are found in small amounts inside typical households, building up over time, but the size of their molecules is too small to be caught by HEPA filters. Since exposure to these chemicals has been linked to cancer, this scientific accomplishment is good news for human health.
In their study published on December 19, 2018 in the journal Environmental Science & Technology, researchers Long Zhang, Ryan Routsong, and Stuart E. Strand described the process they used to modify the pothos ivy plant. The plant was chosen because it was robust and able to grow under many different conditions, and the protein used – P450 2E1, “2E1” for short – is naturally present in all mammals. In humans, 2E1 is in the liver and only turns on to break down alcohol, thus it’s not helpful for breaking down air pollutants. For this reason, the team’s work was focused on making its functionality available outside of the body – they call it a “green liver” concept.
A synthetic version of the 2E1 protein occurring in rabbits was introduced to the pothos ivy so that every cell expressed it. In a test tube trial performed after the genetic modification, chloroform concentration dropped 82 percent after three days, undetectable by six days, and the benzene concentration dropped 75 percent by day eight in vials containing the plants and respective gases. To achieve the benefits of the modified functionality in a household setting, the chemicals will need to be moved to where the plant is located. “If you had a plant growing in the corner of a room, it will have some effect in that room,” Stuart Strand, one of the scientist in the study, said. “But without air flow, it will take a long time for a molecule on the other end of the house to reach the plant.”
Benzene is a common industrial chemical used to make plastics, dyes, detergents, and pesticides, among other things, and is generally found in both rural and urban areas. Its links to cancer are very clear – the most common being leukemia – which has led to significant regulation. While the amount most are exposed to is very low, over time it can build up, especially in areas with heavy traffic, cigarette fumes, and low ventilation. Chloroform is a chemical used that can be released into the air when chlorine is used to clean drinking water, waste water, and swimming pools. Although no direct association between cancer and inhaled exposure to chloroform, the Environmental Protection Agency (EPA) considers it to be a probable human carcinogen due to studies linking high exposure via oral ingestion to cancer.
The process of engineering the plant to function as desired took the team over two years, a significant amount of time compared to the months-long processes of other similar modification projects. However, the time spent was considered to be worthwhile due to both the results achieved and the hardiness of the plant used. They are now working to add the breakdown of formaldehyde to the plant’s capabilities using a different protein. Formaldehyde is a substance present in most building products and tobacco smoke that is also linked to cancer, asthma, and allergies.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
