Inside Anduril and Meta’s quest to make smart glasses for warfare

The defense-tech company Anduril has shared new details about the augmented-reality headset for the military it’s prototyping with Meta, including a vision for ordering drone strikes via eye-tracking and voice commands.

Quay Barnett, who leads the efforts as a vice president at Anduril following a career in the Army’s Special Operations Command, says his fundamental goal is to optimize “the human as a weapons system.” The vision is undoubtedly cyborg-inspired: Barnett wants drones and soldiers to see together, share information seamlessly, and make decisions as one. 

Anduril actually has two such projects in the works. The first is the Army’s Soldier Born Mission Command, or SBMC, for which the company won a $159 million prototyping contract last year to work with Meta on augmented-reality glasses to attach to existing military helmets. But Anduril has also embarked on a self-funded side quest, announced in October, to design its own helmet and headset combo called EagleEye. This is something the military has not asked for, but Anduril insists it will prefer it and purchase it in the end.

So far, both systems are years away. The Army isn’t expected to move its top choice for the SBMC program into production until 2028, if it picks one at all (the previous lead for the effort, Microsoft, was set to receive a $22 billion production contract that was ultimately cancelled when the glasses didn’t prove viable). But Barnett told MIT Technology Review about where both Anduril’s prototypes are headed.

Depending on the situation, the glasses for either prototype will overlay certain information onto a soldier’s field of view. This might be as simple as a compass or as complex as an entire map of the area, information about where nearby drones are flying, or AI-driven recognition of a target like a truck. 

The soldier would then speak to the interface in plain language—for example, to order an evacuation for someone who’s been injured or to plan a route taking into account which areas are off limits. A large language model—Anduril is in tests with Google’s Gemini, Meta’s Llama, and even Anthropic’s Claude, despite the company’s conflict with the Pentagon—will be used to help translate a soldier’s speech into commands the software can follow. And the engine for it all will be Anduril’s software Lattice, which incorporates data from lots of different military hardware into one picture. The Army announced in March that it would spend $20 billion to integrate Lattice with essentially its entire infrastructure.

Barnett’s team is designing the headset to carry out multi-step tasks. A soldier might send a drone to surveil an area and instruct it to come back once it’s found something that looks like an artillery unit; then the system would recommend courses of action, like sending a nearby drone to strike, that would have to be approved by the normal chain of command. Leading the system through this, if all goes to plan, might not even require speech; the soldier could instead communicate through tracked eye movements and subtle taps.

That’s the idea, anyway. It’s worked on early prototypes, Barnett says, but there aren’t yet versions ready for the Army to test at scale. The component parts began arriving in March. Because of federal military contracting rules, these parts—unlike Meta’s commercial smart glasses—required new supply chains that don’t rely on Chinese companies.

It’s a lot for soldiers already bogged down in information overload, says Jonathan Wong, a former US Marine who works as a senior policy researcher at RAND on Army efforts to buy new tech. Both smart glasses projects aim to create a clean interface that presents only the right information at the right time. But it’s a product that soldiers will reject if it costs more of their attention than it saves. “How much mental bandwidth do you have to be both aware of your surroundings and to operate this technology in a way that makes you and your whole unit better?” he says.

Wong recalls that as a platoon commander, for example, he had a radio that operated on three different channels at once. “The moment that two people were on different channels talking at the same time, I immediately couldn’t comprehend anything that either one of them was trying to tell me, and I was probably not aware of my own surroundings,” he says. “I think there are limits to what you can take in.”

Ideally, Barnett says, smart glasses can ease that information overload. Anduril’s approach is to get creative with ways the user can access necessary information quickly. Voice commands and eye tracking are a piece of that strategy. But even if it’s all technically feasible, it might take years of field testing to know if the system is actually useful for soldiers, Wong says. 

Such a system would mark a major escalation in how closely soldiers rely on imperfect AI systems. While computer vision models used to identify objects have long been employed by militaries, and chatbots have recently entered decision-making during the war in Iran, these technologies have not yet made their way to most frontline soldiers. A smart glasses system tasked with identifying threats and recommending strikes would introduce massive new risks of errors. 

Anduril is not the only one competing to develop smart goggles for combat. Rivet, which specializes in wearable sensors for the military, received a $195 million prototyping contract the same time, and in March the Israeli defense-tech company Elbit received its own $120 million contract. This all comes after Microsoft lost its role leading the Army’s smart glasses effort, following a Pentagon audit that found the Army wasn’t properly testing the glasses, a mistake that could have wasted $22 billion.

For both Anduril’s prototypes, the company is testing a new system for digital night vision, which uses electronic sensors and algorithms to boost low levels of light. It’s been a promised technology for decades but has tended to work too slowly for practical use and produce grainy images. Anduril says it has found improvements over previous prototypes through techniques rooted in both new generative AI and older machine learning. 

Much of the other hardware for both projects is being built by Meta, including the displays and the waveguides that send visuals to the user’s eye without blocking the view. That might be a surprise to anyone who knows the backstory: In 2017, Facebook (now Meta) ousted Anduril founder Palmer Luckey following an internal conflict involving his support for Donald Trump. The two are now back in the augmented-reality business together, while Mark Zuckerberg has also adopted a friendlier posture toward the second Trump administration.

For the Army initiative, this suite of smart glasses, night vision, and sensors will be attached to the helmets and other gear soldiers already wear, with a separate battery pack. The EagleEye version will instead incorporate the tech into the helmet itself. Even if the Army doesn’t prefer EagleEye in the end, Barnett says, Anduril will attempt to sell the system to foreign militaries.

Multiple challenges must still be overcome. Unlike Meta’s Ray-Ban glasses, the prototypes have to operate in an environment full of dust, explosions, and smoke. Adding the computing power and battery life they need also means more weight for soldiers already carrying upwards of 100 pounds. Then the technology has to work in environments without ubiquitous 5G cell connections; powerful computer vision and AI models will need to run locally on the device.

For the Army to want to buy it at scale, “it’s got to work, and it’s got to be pretty seamless,” Wong says. “It’s a high bar.”

Genetic and clinical investigation of insulin-degrading enzyme in Parkinson’s disease within the Chinese Han population

IntroductionGrowing evidence suggests a mechanistic link between type 2 diabetes mellitus and Parkinson’s disease (PD), with insulin-degrading enzyme (IDE) implicated in both insulin and amyloid-β metabolism, as well as α-synuclein degradation. However, the role of IDE in PD pathogenesis remains insufficiently defined. This study aimed to investigate the association of IDE gene polymorphisms and serum IDE levels with sporadic PD in a Chinese Han population.MethodsFourteen single nucleotide polymorphisms (SNPs) within the IDE gene were genotyped in 463 patients with sporadic PD and 576 age- and sex-matched healthy controls (HCs). An independent cohort of 100 PD patients and 100 HCs was used to quantify serum IDE concentrations. Correlations between IDE levels and clinical features were assessed. Logistic regression was employed to identify independent factors associated with PD.ResultsAmong the examined SNPs, rs11187007 showed a nominal allelic association with PD (P = 0.046), which did not survive the Bonferroni correction. Serum IDE concentrations were significantly higher in PD patients than in HCs (P = 0.015). Elevated IDE levels were negatively correlated with Mini-Mental State Examination scores (R = –0.230, P = 0.027) and positively associated with more severe symptoms. Logistic regression indicated that elevated serum IDE levels were associated with PD.ConclusionOur findings highlight that elevated serum IDE correlates with PD, suggesting a role for IDE in neurodegeneration, warranting further mechanistic and longitudinal studies to evaluate its potential as a therapeutic target in PD.

From autophagy–lysosomal deficits to neurodegeneration in Niemann-Pick type C1 disease: implications for age-related neurodegenerative disorders

Niemann-Pick type C1 (NPC1) disease is a neurodegenerative lysosomal storage disorder caused by loss-of-function mutations in the NPC1 gene. NPC1 deficit primarily disrupts lipid homeostasis and subsequently drives cellular degeneration through mechanisms involving impaired autophagy and mitophagy, mitochondrial dysfunction, and, recently demonstrated NAD depletion that links autophagy impairment to neuronal death. Emerging evidence also highlights the activation of innate immune signaling leading to neuroinflammation. In this review, we synthesize current mechanistic insights and describe how these molecular deficits are interconnected to drive neuronal death in NPC1 disease. We also discuss how these pathological processes parallel those observed in major age-related neurodegenerative pathologies such as Alzheimer’s and Parkinson’s disease. Finally, we highlight emerging therapeutic strategies that can potentially ameliorate these cellular deficits, offering avenues for mitigating neurodegeneration in NPC1 disease and other related neurodegenerative disorders.

Effects of motor imagery brain-computer interface task on quantitative EEG features in patients with prolonged disorders of consciousness

ObjectiveTo analyze quantitative electroencephalographic (EEG) characteristics during Motor Imagery Brain-Computer Interface (MI-BCI) task in patients with prolonged disorders of consciousness (pDoC).MethodsForty-three patients with pDoC due to various brain injuries were enrolled. Based on modified Coma Recovery Scale-Revised (CRS-R) assessments, the patients were divided into 19 in the unresponsive wakefulness syndrome (UWS) group and 24 in the minimally conscious state (MCS) group. All patients underwent 5 min of resting-state (RS) EEG followed by 5 min of MI-BCI task. Relative power, DTABR, and average brain engagement (BE) during MI-BCI were analyzed across resting and MI-BCI states using Fast Fourier Transform (FFT) spectra.ResultsMixed-design ANOVA showed significant main effects of condition and group across all EEG frequency bands, indicating clear differences between the RS and MI-BCI conditions and between UWS and MCS patients. Significant group × condition interactions were found in the delta, beta, and gamma bands, as well as in DTABR. Simple effects analysis showed that delta power was higher in RS than in MI-BCI in both groups, with UWS consistently exhibiting higher delta power than MCS under both conditions. In contrast, beta and gamma power were higher in MI-BCI than in RS in both groups. For beta power, UWS was higher than MCS under RS, whereas MCS was higher than UWS under MI-BCI, showing a reversal of the interaction pattern. For gamma power, MCS showed higher values than UWS under both conditions, with a larger between-group difference during MI-BCI. DTABR was significantly higher in RS than in MI-BCI in both groups; however, MCS exhibited higher DTABR than UWS under RS, whereas the opposite pattern was observed under MI-BCI. In addition, during MI-BCI tasks, the MCS group showed greater average BE than the UWS group.ConclusionMI-BCI shows potential as a diagnostic or assessment tool for evaluating the level of consciousness in patients with pDoC.

Amelioration of tic disorder by Jujuboside A via gut microbiota remodeling and intestinal 5-HT signaling

BackgroundTic disorder (TD) is a common chronic neuropsychiatric condition manifesting during childhood and adolescence. Jujuboside A (JuA) may alleviate TD symptoms; however, the mechanisms underlying its therapeutic effects remain unclear.MethodsWe established a rat model of TD and used histological techniques to evaluate the effects of JuA on pathological changes. We also measured 5-hydroxytryptamine (5-HT) and 5-hydroxyindoleacetic acid (5-HIAA) levels and assessed tryptophan hydroxylase 1 (TPH1) mRNA expression. Finally, we analyzed the gut microbiota composition in fecal samples using 16S rRNA metagenomic sequencing.ResultsJuA administration alleviated pathological changes in rats with TD, increased 5-HT and 5-HIAA levels, and upregulated TPH1 mRNA expression. Compared with no treatment, JuA treatment increased the proportion of Bacteroidia, Muribaculaceae, Bacteroidales, and Bacteroidota, while reducing that of Bacilli, Lactobacillaceae, Lactobacillus, Lactobacillales, and Firmicutes.ConclusionThese findings indicate that JuA mitigates TD progression, potentially by remodeling the gut microbiota and regulating 5-HT levels.

Multivariate age-related variations in quantitative MRI maps: widespread age-related differences revisited

This study applied multivariate ANOVA to investigate age-related microstructural changes in the brain tissues driven primarily by myelin, iron, and water content, as observed in MRI (semi-)quantitative R1, R2*, MTsat and PD maps. This is effectively a re-analysis of the data analyzed in a univariate way in a previous publication. Voxel-wise analyses were performed on gray matter (GM) and white matter (WM), in addition to region of interest (ROI) analyses. The multivariate approach identified brain regions showing coordinated alterations in multiple tissue properties and demonstrated bidirectional correlations between age and all examined modalities in various brain regions, including the caudate nucleus, putamen, insula, cerebellum, lingual gyri, hippocampus, and olfactory bulb. The multivariate model was more sensitive than univariate analyses, as evidenced by detecting a larger number of significant voxels within clusters in the supplementary motor area, frontal cortex, hippocampus, amygdala, occipital cortex, and cerebellum bilaterally. Though when cross validating the results by splitting the data into 2 subsets, sensitivity is strongly reduced, even more so for the multivariate approach. The examination of normalized, smoothed, and z-transformed maps within the ROIs revealed concurrent age-dependent alterations in myelin, iron, and water content. These findings contribute to our understanding of age-related brain differences and provide insights into the underlying mechanisms of aging. The study emphasizes the importance of multivariate analysis for detecting subtle microstructural changes associated with aging when dealing with multiple quantitative MRI parameter maps.

Neurocognitive function among individuals with problematic social media use

BackgroundWith the development of technology and the internet, social networks gained momentum quickly and play a central role in daily activities. Despite this, there is a public health concern over excessive or problematic social media use. There is also a debate whether excessive social media use should be considered as a behavioral addiction characterized by impulsivity or an impulse control disorder characterized by compulsivity. The goal of this study is to use neurocognitive tasks to investigate impulsivity and compulsivity among excessive social media users compared with non-excessive users.MethodThe study included 79 participants (age range 18 to 37), divided into two groups: 34 participants who excessively use social media (Mean Age = 23.03, SD = 2.71) and 45 participants who do not excessively use social media (Mean Age = 25.47, SD = 4.3). Participants filled out a demographic questionnaire, questionnaires on social media use, impulsivity, compulsivity, anxiety, and depression. They performed computerized cognitive tasks: GO/NO-GO (with Facebook and traffic sign pictures), Experimental Delay Discounting (EDT), and the Wisconsin Card Sorting Test (WCST).ResultsExcessive users of social media exhibited a lower ability to delay gratification on the EDT, indicating impulsivity. They made fewer non-perseverative errors on the WCST, which indicated high flexibility and test shifting, which is a contradicting evidence for compulsivity. Furthermore, on the GO/NO-GO task, individuals who excessively use social media made more omission errors in response to the “Facebook” sign compared to traffic signs (GO condition), indicating impaired selective attention. Finally, they also showed higher subjective ratings of anxiety, depression, impulsivity, and compulsivity.DiscussionThe results of this study provide evidence for impulsivity indicated by delay discounting tendency, which supports the behavioral addiction model, impaired selection attention and lack of evidence for compulsivity in excessive social media users. Further research on neurocognitive function in excessive social media users is required in order to determine whether it should be considered a behavioral addiction or an impulse control disorder.

Heatwave-related variations in psychiatric consultations and admissions: a time-series analysis

BackgroundHeatwaves are becoming increasingly frequent and intense across Europe, posing significant risks to physical and mental health. Emerging evidence suggests that prolonged exposure to high temperatures may exacerbate psychiatric symptoms and increase the demand for acute mental health services.ObjectivesThis study examined the relationship between extreme heat events and psychiatric service utilization in Bolzano, Italy, by analyzing emergency psychiatric consultations and acute psychiatric admissions across three non-consecutive years.MethodsA retrospective observational analysis was conducted using daily psychiatric consultations in the Emergency Department (ED) and daily admissions to acute psychiatric wards from 2013, 2018, and 2023. Meteorological data were obtained from the provincial environmental agency. Time-series analyses employed ARIMA models, incorporating daily minimum and maximum temperatures, tropical nights, and a cumulative heatwave index (n_hot_htwv). Model selection was based on BIC, and the effect of exogenous temperature variables was evaluated through changes in AIC. Residual diagnostics guided the inclusion of weekly seasonal dummy variables.ResultsNon-seasonal ARIMA models with day-of-week dummies provided the best fit for both consultations and admissions. Adding the cumulative heatwave variable (n_hot_htwv) consistently improved model fit across all years, whereas minimum and maximum temperatures alone did not. Heatwave duration emerged as a more sensitive predictor of psychiatric service utilization than isolated temperature peaks. No evidence of yearly seasonality was found, and residual diagnostics supported the robustness of models including weekly dummy variables.ConclusionHeatwaves are associated with increased psychiatric consultations and hospital admissions in Bolzano, with cumulative heat exposure representing a critical determinant. These effects cannot be explained solely by seasonal patterns, suggesting an independent climatic influence. Given the projected rise in heatwave intensity and duration, mental health services should incorporate climate-responsive planning and early-warning strategies.

Psychological inflexibility and resilience in anxiety: insights from machine-learning and robust mediation-based models

IntroductionPsychological inflexibility (PI) has been associated with anxiety symptoms, while resilience serves as a protective factor; however, their roles and interrelationship remain poorly understood. We investigated the role of PI on anxiety-related symptoms while assessing the mediating role of resilience and testing the moderating effect of sex and psychiatric history.MethodsFrom April to July 2021, an online protocol employing self-reported measures assessed PI (Acceptance and Action Questionnaire), resilience dimensions (Resilience Scale for Adults), and anxiety-related symptoms (Generalized Anxiety Disorder (GAD) Scale; Depression, Anxiety, and Stress Scales). A model generation approach, using machine-learning and robust mediation-based models, was applied to investigate the relationships between these constructs.ResultsIn a sample of 313 adults (72.20% females; 39.29 ± 11.81 years), Random Forest analysis indicated PI and the resilience dimensions perception of self (R-PS) and planned future (R-PF) as the strongest predictors of anxiety-related symptoms. PI showed a positive direct association with GAD, anxiety, and stress (respectively β = 0.28, β = 0.07, β = 0.20, p ≤ 0.001). Significant indirect associations emerged: PI–Stress regarding R-PS (β = 0.08, p = 0.004), PI–Anxiety regarding R-PF (β = 0.03; p = 0.03), PI–GAD (β = 0.08, p = 0.001) and PI–Stress (β = 0.11, p < 0.001) regarding R-PS and R-PF together.DiscussionThese findings highlight the importance of PI and resilience as interconnected processes underlying mental health outcomes. Additionally, they suggest that psychological intervention programs targeting PI, along with resilience, could foster healthier strategies for coping with anxiety-related symptoms.