Whenever I used to think about brain-computer interfaces (BCI), I typically imagined a world where the Internet was served up directly to my mind through cyborg-style neural implants—or basically how it’s portrayed in Ghost in the Shell. In that world, you can read, write, and speak to others without needing to lift a finger or open your mouth. It sounds fantastical, but the more I learn about BCI, the more I’ve come to realize that this wish list of functions is really only the tip of the iceberg. And when AR and VR converge with the consumer-ready BCI of the future, the world will be much stranger than fiction.
Be it Elon Musk’s latest company Neuralink —which is creating “minimally invasive” neural implants to suit a wide range of potential future applications, or Facebook directly funding research on decoding speech from the human brain—BCI seems to be taking an important step forward in its maturity. And while these well-funded companies can only push the technology forward for its use as a medical devices today thanks to regulatory hoops governing implants and their relative safety, eventually the technology will get to a point when it’s both safe and cheap enough to land into the brainpan’s of neurotypical consumers.
Although there’s really no telling when you or I will be able to pop into an office for an outpatient implant procedure (much like how corrective laser eye surgery is done today), we know at least that this particular future will undoubtedly come alongside significant advances in augmented and virtual reality. But before we consider where that future might lead us, let’s take a look at where things are today.
Classical biomedical data science models are trained on a single modality and aimed at one specific task. However, the exponential increase in the size and capabilities of the foundation models inside and outside medicine shows a shift toward task-agnostic models using large-scale, often internet-based, data. Recent research into smaller foundation models trained on specific literature, such as programming textbooks, demonstrated that they can display capabilities similar to or superior to large generalist models, suggesting a potential middle ground between small task-specific and large foundation models. This study attempts to introduce a domain-specific multimodal model, Congress of Neurological Surgeons (CNS)-Contrastive Language-Image Pretraining (CLIP), developed for neurosurgical applications, leveraging data exclusively from Neurosurgery Publications.
METHODS:
We constructed a multimodal data set of articles from Neurosurgery Publications through PDF data collection and figure-caption extraction using an artificial intelligence pipeline for quality control. Our final data set included 24 021 figure-caption pairs. We then developed a fine-tuning protocol for the OpenAI CLIP model. The model was evaluated on tasks including neurosurgical information retrieval, computed tomography imaging classification, and zero-shot ImageNet classification.
Self-driving cars which eliminate traffic jams, getting a health care diagnosis instantly without leaving your home, or feeling the touch of loved ones based across the continent may sound like the stuff of science fiction.
But new research, led by the University of Bristol and published in the journal Nature Electronics, could make all this and more a step closer to reality thanks to a radical breakthrough in semiconductor technology.
The futuristic concepts rely on the ability to communicate and transfer vast volumes of data much faster than existing networks. So physicists have developed an innovative way to accelerate this process between scores of users, potentially across the globe.
Dear Friends and Colleagues, this issue of the Security & Insights newsletter focuses on cybersecurity and the convergence of devices and networks. The convergence of the Internet of Things, industrial control systems (ICS), operational technology (OT), and information technology (IT) has revealed vulnerabilities and expanded attack surfaces. They are prime targets for hackers, who frequently look for unprotected ports and systems on internet-connected industrial devices. Because they provide several avenues of entry for attackers and because older OT systems were not built to withstand cyberattacks, IT/OT/ICS supply chains in continuous integration (CI) are especially vulnerable. Below is a collection of articles that address the challenges and threats of cybersecurity for connected devices and people.
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We, of course, feel “internal experiences,” that thing we call self, and we know very well when we’ve woken up. Consciousness, in fact, is what we lose when we fall asleep and regain when we wake up. ChatGPT 4.0 is emulating those human feelings. That doesn’t mean it actually feels them. But what if it does feel them one day? Will we listen to it then?
Schneider is among the intellectuals who believe that the question of machine consciousness is worth examining in depth. Not because she believes we’re already there, but because she believes it will happen sooner or later. Like Hassabis, she estimates that artificial general intelligence (AGI) — the name computer scientists give to something close enough to human intelligence to escape the simulacrum label and access a qualitatively different level — is a few decades away.
AGI will be a system capable of learning from experience without having to swallow the entire internet before breakfast; capable of abstracting information, projecting actions, and understanding situations it has never encountered before. And yes, perhaps capable of having “inner experiences,” or what we might call a form of consciousness. Don’t take it out on me; it’s philosophers who are examining this question.
