News
US Department of Defense commits $2B to training AI to have “common sense”
While artificial intelligence is being painted by companies and government as the catch-all answer to many of today’s inefficiencies and problems, it currently has one glaring shortcoming: It can’t answer common sense questions.
In an effort to address this current shortcoming of AI, The U.S. Department of Defense (DoD) is committing $2 billion dollars over the next five years to its Machine Common Sense (MCS) Program. The program aims to enable computers to communicate naturally, behave reasonably in new situations, and learn from new experiences.
Thanks in part to Iron Man (and Elon Musk) fame, the Defense Advanced Research Projects Agency, aka “DARPA”, an agency within the DoD, may be one of the few alphabet soup government agencies with a future-tech-savvy reputation. That reputation is well deserved, too, if history has anything to say about it. As the agency that gave us the Internet through an extension of a defense communication project, just having a discussion online about DARPA itself is testament to the tech potential it represents. The challenge of creating true, thinking computers is perfectly aligned with what DARPA has done well with overall.
As the advancement of computer technology increases at a near exponential rate, so too has the potential relationship between them and humans. However, the possibility of a troubling disconnect is also a growing reality. In other words, humans and computers currently operate very differently from one another, and that could spell bad things for the weaker logician of the two. Yeah, that means us.
Elon Musk has famously harped about this predicted disconnect on numerous occasions, and one of the companies he’s invested in, Neuralink, is working on preemptive solutions for its coming problems. While Neuralink generally aims to help human brains work more like computers, DARPA is taking the approach of having computers work more like humans.
The term “common sense” can often be tossed around in conversations to imply a variety of shared knowledge bases, but as a federal government agency, DARPA has its own specific definition for this context: “The basic ability to perceive, understand, and judge things that are shared by nearly all people and can be reasonably expected of nearly all people without need for debate.” By mimicking the cognitive processes we go through when we are young, the agency hopes computers will develop the “fundamental building blocks of intelligence and common sense” just like a human.
With advanced neural networks making amazing (and humorous) headlines regularly, what would a “common sense” machine bring to the table in terms of advancement? One primary answer is the requirement for less initial information. To quote Dr. Brian Pierce, director of DARPA’s Innovation Office, at a recent summit, “We’d like to get away from having an enormous amount of data to train neural networks.” If a machine could use its environment to deduct answers when compared to its existing knowledge base, as humans do, it wouldn’t need to be taught to interpret data solely based on an enormous amount of data previously provided. Essentially, it could think for itself using common sense.
DARPA has now completed a “Proposers Day” wherein potential contractors were presented with the agency’s specifics for its MCS program. The next step is a “Broad Agency Announcement”, i.e., a formal invitation for proposals to work on the project with the hope of obtaining a federal contract to fulfill its aim.
If the contract winner is successful, will common sense lead to computer behavior we’d welcome rather than fear? Hopefully that will be figured out sooner rather than later.
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.”
News
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
