How your WiFi router helps AI read your mind….

Your wifi Router helps AI read your mind

How your WiFi router helps AI read your mind…. (side note: You wait until they start talking about sleep interrogation technology which they’ve had for a very long time

How your WiFi router helps AI read your mind…. 

(side note: You wait until they start talking about sleep interrogation technology which they’ve had for a very long time

 

WiFi is a two-way form of communication: Your router carries internet data to your laptop, which then transmits data back to the router en route to the internet. An EQ-Radio measures the speed at which data completes a round trip to its target — for example, you — and analyzes fluctuations in that speed to measure your heart rate. It’s your heart rate that gives away your emotional state.

The correlation of heartbeat to emotion in each person is unique to some extent, but MIT says they can accurately assess the emotional state even of people they’ve never before studied 70% of the time. Mingmin Zhao, on the MIT team, told MIT News, “Just by knowing how people breathe and how their hearts beat in different emotional states, we can look at a random person’s heartbeat and reliably detect their emotions.”

BrainGPT thoughts to text – how AI can read your mind

If you thought that you had to lie inside an fMRI machine for AI to puzzle your mind, think again. BrainGPT systems have become portable.

BrainGPT – a “mind-reading” app – is significantly closer than you might have imagined.
• A significant advance in sensor technology has made BrainGPT a portable prospect.
• At the moment, it’s a technology with around a 40% accuracy – but speech recognition moved quickly, and so could this.

Volunteers used to have to lie inside an fMRI machine and listen to podcasts before large language models (LLMs) could decode their thoughts. But not anymore. Portable, high-performance multichannel wireless EEG acquisition systems have been shown to be capable of BrainGPT-enabled thought-to-text conversion, which is a big deal.

The team behind the latest breakthrough – a group of researchers based at the Human-centric Artificial Intelligence Center in Sydney, Australia – presented their results at NeurIPS 2023, which took place this week in the US.

behavior of each network agent. In contrast, the author of [16] proposed a Collaborative RL (CRL)-based

routing algorithm with no single global state. The CRL approach was also successfully applied for delay-

tolerant network routing in [17]. However, in an inherently distributed system, state synchronization

among all routers is extremely difficult, especially with increasing network size, speed, and load. With

the development of SDN technology, centralized AI-driven routing strategies have received considerable

 

attention.

2.2 Centralized Routing

In [18], Stampa et al. proposed a deep RL (DRL) algorithm for optimizing routing in a centralized

knowledge plane. Benefiting from the global control perspective, the experimental results showed very

promising performance. In [19], Lin et al. applied the SARSA algorithm to achieve QoS-aware adaptive

 

routing in multilayer hierarchical software-defined networks. For each flow, the controller updated the

optimal routing strategy based on the QoS requirements and issued the forwarding table to each node

along the forwarding path. In [20], Wang et al. proposed a RL-based routing algorithm for Wireless Sensor

Networks (WSNs) named AdaR. In AdaR, Least-Squares Policy Iteration (LSPI) is implemented to achieve

 

the correct tradeoff among multiple optimization goals, such as the routing path length, load balance, and

retransmission rate. However, the overhead incurred for centralized AI control is high.

3 AI-DRIVEN NET WORK ROUTING

In this section, we first propose a three-layer logical functionality architecture for AI-driven networking.

Then, we discuss the problem of how far away the intelligent control plane can be located from the

Mind-reading AI turns thoughts into words using a brain implant