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The QCD vacuum (i.e., the ground state of vacuum in the quantum chromodynamics regime) is theoretically characterized by the presence of non-zero expectation values of condensates, such as gluons and quark–antiquark pairs. Instead of being associated with a lack of particles and interactions in an empty space, physics theory regards this state as filled with the so-called condensates, which have the same quantum numbers as the vacuum and cannot be directly observed.

While many have discussed the properties of the QCD vacuum, experimentally validating these theoretical predictions has so far proved challenging, simply because the condensates in this state are elusive and cannot be directly detected. A hint of experimental “observation” can be found in the theoretical predictions of the properties of the QCD vacuum.

Theories predict that the condensate may decrease in the high temperature and/or at a high matter due to the partial restoration of the so-called chiral symmetry. To prove these theories, some researchers collected measurements during ultra-relativistic, head-on collisions of heavy ions at particularly high temperatures. Other efforts in this area tried to probe properties of the QCD vacuum by measuring so-called “medium effects.” These are essentially effects that alter the QCD vacuum and its structure, prompted by the presence of high matter density such as nuclear matter.

Michael Levin’s 2019 paper “The Computational Boundary of a Self” is discussed. The main topics of conversation include Scale-Free Cognition, Surprise & Stress, and the Morphogenetic Field. Michael Levin is a scientist at Tufts University; his lab studies anatomical and behavioral decision-making at multiple scales of biological, artificial, and hybrid systems. He works at the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science.

🚩The Computational Boundary of a Self: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition (can read in browser or download as pdf)
https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02688/full.

❶ Scale-Free Cognition.
3:05 Ultimate question of the embodied mind.
5:50 The most difficult interview to prepare for.
6:55 One of my favorite papers of all time (screenshare)
7:40 The Computational Boundary of a Self.
9:25 Defining intelligence (cybernetics)
10:30 Cognitive light cones.
16:50 All intelligence is collective intelligence.
17:35 Nested selves vs. one integrated self (Not Integrated Information Theory)
21:10 The same dynamics in the brain occur in every tissue of the body.
22:50 Why scale “free” cognition?

❷ Stress & Surprise.

Many current computational models that aim to simulate cortical and hippocampal modules of the brain depend on artificial neural networks. However, such classical or even deep neural networks are very slow, sometimes taking thousands of trials to obtain the final response with a considerable amount of error. The need for a large number of trials at learning and the inaccurate output responses are due to the complexity of the input cue and the biological processes being simulated. This article proposes a computational model for an intact and a lesioned cortico-hippocampal system using quantum-inspired neural networks. This cortico-hippocampal computational quantum-inspired (CHCQI) model simulates cortical and hippocampal modules by using adaptively updated neural networks entangled with quantum circuits. The proposed model is used to simulate various classical conditioning tasks related to biological processes. The output of the simulated tasks yielded the desired responses quickly and efficiently compared with other computational models, including the recently published Green model.

Several researchers have proposed models that combine artificial neural networks (ANNs) or quantum neural networks (QNNs) with various other ingredients. For example, Haykin (1999) and Bishop (1995) developed multilevel activation function QNNs using the quantum linear superposition feature (Bonnell and Papini, 1997).

The prime factorization algorithm of Shor was used to illustrate the basic workings of QNNs (Shor, 1994). Shor’s algorithm uses quantum computations by quantum gates to provide the potential power for quantum computers (Bocharov et al., 2017; Dridi and Alghassi, 2017; Demirci et al., 2018; Jiang et al., 2018). Meanwhile, the work of Kak (1995) focused on the relationship between quantum mechanics principles and ANNs. Kak introduced the first quantum network based on the principles of neural networks, combining quantum computation with convolutional neural networks to produce quantum neural computation (Kak, 1995; Zhou, 2010). Since then, a myriad of QNN models have been proposed, such as those of Zhou (2010) and Schuld et al. (2014).

Scientists at MIT have unlocked a major breakthrough in the battle to reverse the effects of Alzheimer’s disease — one that shows “dramatic reductions” in neurodegeneration, a report stated. The exciting achievement came about after researchers were able to interfere with an enzyme typically found to be overactive in the brains of Alzheimer’s patients.

OpenAI’s breakthrough consistency model will lead into image understanding to make GPT4 multimodal, providing next generation improvements with human-computer interaction, human-robot interaction, and even helping the disabled. Microsoft has already released a predecessor to GPT4 image understanding by with Visual ChatGPT, which is much more limited in its abilities.

Deep Learning AI Specialization: https://imp.i384100.net/GET-STARTED
AI Marketplace: https://taimine.com/

AI news timestamps:
0:00 Multimodal artificial intelligence.
0:35 OpenAI consistency models.
1:35 GPT4 and computers.
3:04 GPT4 and robotics.
4:28 GPT4 and the disabled.
5:36 Microsoft Visual ChatGPT

#ai #future #tech

Called the nanofluidic drug-eluting seed (NDES), it delivers low-dose immunotherapy in the form of CD40 monoclonal antibodies (mAb).

In a significant groundbreaking medical development, researchers have created a tiny device, smaller than a grain of rice, to deliver drugs directly to the pancreatic tumor.

Nano-device uses less dosage to shrink cancer.


Houston Methodist.

The agency will look at developing a standard policy for setting privacy rules on artificial intelligence.

AI-enabled language models are becoming commonplace of late, spearheaded by the disruption caused by OpenAI’s ChatGPT. In its wake, we have seen other technological players like Google and Microsoft scrambling to catch up to the competition by introducing their respective models to the public.

As a counterbalance, global authorities are doing due diligence to evolve a common framework to regulate the industry.


Ipopba/iStock.

Its demonstration nuclear power plant is expected to be ready by 2035.

The Experimental Advanced Superconducting Tokamak (EAST), popularly known as China’s “artificial sun”, set a new record on Wednesday by running for 403 seconds in a steady-state high-confinement long plasma operation, Chinese news outlet CGTN

Moving closer to nuclear fusion energy.


Institute of Plasma Physics.

This has important implications for measuring the mass of the central black hole in M87.

Look at the image on the left and then the image on the right. They are by no means identical. But what if we told you that both the images are of the same object?

The object being a supermassive black hole.


NoirLab.