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DARPA-winning robotics team faces boycott over interest in AI weapons development
South Korea’s KAIST University, the school behind the advanced humanoid DRC-HUBO robot that won DARPA’s 2015 Robotics Challenge, is facing a boycott from some of the world’s top AI researchers. The boycott comes amid reports that KAIST is developing AI weapons in collaboration with South Korean defense company Hanhwa Systems.
The boycott against KAIST is headed by Professor Toby Walsh of the University of New South Wales, who stated that the university’s work with Hanhwa, a known weapons developer in S.Korea, stands as one of the signs that the arms race for autonomous weapons is beginning. According to Walsh, him and 49 of his peers across 30 different nations are unanimous in the notion that KAIST’s initiatives will only accelerate the AI weapons race.
“We can see prototypes of autonomous weapons under development today by many nations including the US, China, Russia, and the UK. We are locked into an arms race that no one wants to happen. KAIST’s actions will only accelerate this arms race. We cannot tolerate this. This is a very respected university partnering with a very ethically dubious partner that continues to violate international norms,” Walsh said, according to a report from The Verge.
Under the terms of the boycott, all contact and collaboration with KAIST would be forbidden. These academic sanctions will be enforced until the South Korean university can assure that the weapons it will develop will have a form of “meaningful human control.”
KAIST President Sung-Chul Shin, however, argues that the university is not engaged in any programs that will result in the development of deadly AI-powered robots.
“I would like to reaffirm that KAIST does not have any intention to engage in development of lethal autonomous weapons systems and killer robots. I reaffirm once again that KAIST will not conduct any research activities counter to human dignity including autonomous weapons lacking meaningful human control,” Shin said.
KAIST’s projects with Hanhwa Systems came into light after a report from The Korea Times. According to the publication, 25 researchers from KAIST will be working with the weapons maker in order to develop AI arms, which would be capable of searching for and eliminating targets without human control. Among the weapons mentioned in the report are AI-based missiles that can control their altitude as well as AI-equipped unmanned submarines and quadcopters.
KAIST’s prowess in robotics were in full show in 2015, when the South Korean university joined DARPA’s Robotics Challenge. During the competition, the team’s biped robot, dubbed the DRC-HUBO, bested its competitors by achieving a perfect score in an obstacle course. KAIST won $2 million as a result of its efforts.
As we noted in a previous report, Tesla CEO Elon Musk has been vocal about his reservations on the dangers of unregulated AI. Just last year, Musk boldly stated that the next world war might be caused by the spread and the advent of over-advanced, uncontrolled artificial intelligence. Considering the nature of the projects being conducted by KAIST and Hanhwa, Musk’s apprehension about the risks of AI does appear to be well-founded.
A look at futuristic military combat robots from the US Miliary’s Research Labs.
Elon Musk
Tesla Semi finally has an FSD timeline and it’s waiting on the Cybercab
Elon Musk told investors Semi self-driving should start working by early 2027, per today’s earnings.
During Wednesday’s’ Tesla Q2 earnings call, an analyst asked Elon Musk when Tesla would look at autonomy for the Semi. His answer set a real timeline for the first time, noting that self-driving on the Tesla Semi is expected to start working “around the end of this year or early next year”.
Musk framed the delay as a matter of priority, not capability. Tesla’s self-driving team is currently focused on Model 3, Model Y, and Cybercab, the vehicles that make up the overwhelming majority of Tesla’s fleet. Since Semi trucks on the road remain a small fraction of that total even after the recent Nevada factory ramp, Musk said it made more sense to keep the software team’s attention on what he called “the march of nines of safety” for the higher volume vehicles first. Autonomous Semi development is “taking a bit of a backseat for the next six months or so,” he said, before adding that it “will definitely be working next year and in time for the scale-up to high production of the Tesla Semi.”
Tesla Semi’s official battery capacity leaked by California regulators
The timeline lines up with what’s already been showing up on public roads. In June, a Tesla Semi was spotted in Sunnyvale wearing a full validation rig, the same rooftop sensor array Tesla mounts on vehicles ahead of an FSD milestone.
A second unit was seen near Fremont days later with a matching camera suite and lens washers. Separately, Tesla analyst Nic Cruz Patane posted video this month of the production Semi’s exterior camera array, ten AI4 based units built directly into the truck rather than added later.
Tesla Semi AI4 cameras. The production version has 10 cameras on its exterior.
These trucks are designed to be autonomous. pic.twitter.com/GH3BamxIBQ
— Nic Cruz Patane (@niccruzpatane) April 14, 2026
Musk also gave the reason autonomy on the Semi matters in the first place, a persistent shortage of qualified truck drivers. “There is a really serious shortage of truckers,” he said on the call, framing a self-driving Semi as important both for addressing that shortage and for improving safety and comfort for the drivers running the truck today.
The timing also tracks with the Semi’s production reality. Tesla’s Q2 shareholder letter, dropped language promising the Semi would reach volume production this year. Musk pointed to 4680 battery cell output as the near-term constraint on Semi and Cybercab production. A software timeline landing in early 2027 gives Tesla’s autonomy team room to work while the hardware ramp catches up behind it.
It’s worth nothing that this isn’t necessarily a promise the Semi ships driverless next year. Musk’s own language, self-driving “working” by early 2027, describes internal validation catching up to hardware already riding on every production truck, not a public unsupervised rollout.
Investor's Corner
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.
The earnings results come after Tesla reported a massive beat on vehicle deliveries for the second quarter, delivering 489,126 vehicles and building 451,758 cars during the three-month span.
This was a major shock for those on Wall Street as they anticipated somewhere around 400,000 deliveries for the quarter, and showed Tesla still has plenty of demand for its vehicles around the world and in the U.S. despite losing the $7,500 EV Tax Credit last year.
Tesla Q2 2026 Earnings Results
- Non-GAAP EPS – $0.33 reported vs. $0.53 expected
- Revenues – $28.236 billion reported vs. $26.4 billion expected
- Free Cash Flow- -$1.092B
- Profit -$ 4.751B
Tesla (beat/missed) analyst expectations, so the market response to the company’s quarter is what we will look for next.
Tesla shares closed today down just over 1 percent, trading at $374.01.
In the past, it has been anyone’s guess with what Tesla shares will do after they report earnings. Strong quarters have resulted in sharp drops, while lackluster quarters have seen the stock shoot up considerably.
Tesla will hold its Q2 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.
You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.
Q2 2026 Earnings Call https://t.co/zZS6ii2TWK
— Tesla (@Tesla) July 22, 2026
Elon Musk
Tesla is about to make parking in busy lots less stressful than ever
Tesla is about to make parking in busy parking lots at businesses and other points of interest less stressful than ever by allowing drivers more control over where they park and how, CEO Elon Musk confirmed on X.
Tesla has been working to improve the parking performance of vehicles utilizing the Full Self-Driving suite, but now it is looking to add more customization, allowing drivers to choose the specific space they park in, but also potentially the orientation the car pulls into the spot:
It’s coming soon
— Elon Musk (@elonmusk) July 21, 2026
Musk has reiterated on X twice over the past several weeks that Tesla is working to make things with the FSD suite based more on the driver’s specific preferences and behaviors that were seen in past drives.
Essentially, it sounds like if you tend to park away from a business to avoid other vehicles, Tesla FSD will soon recognize that preference of yours and start parking further away as well. Additionally, the prospect of assigned parking spaces has been something many owners have voiced concerns about.
Living in a community with assigned parking spaces makes using FSD incredibly difficult as it will rarely park in the correct spot when there are so many to choose from. This is also pertinent in work settings where there are sometimes assigned parking spaces.
The updates to Tesla’s Full Self-Driving suite in terms of listening to driver preferences with parking are also extending to routing. Tesla announced yesterday that with the release of its 2026 Summer Update, it was adding Automatic Navigation and Preferred Routes:
Tesla reveals 2026 Summer Update with crazy fixes to Nav and more
Tesla has always maintained the idea that any human input is bad input, and that, ideally, Tesla Full Self-Driving will always make the right decision. Of course, this is all in theory, but the issue is that so many of Tesla’s interventions have come because it does something that is not necessarily wrong, but perhaps not what the driver would prefer.
Taking these preferences into account will help Tesla alleviate some of the potentially unnecessary interventions that drivers perform.
