Ok, I’ll offer some format and spelling fixes.
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“this has definitely come up in discussions. Non-profits were initially exempt from complying with data requests, but are set to kick in. We’re keeping a close eye on it.”
“this has definitely come up in discussions. Non-profits were initially exempt from complying with data requests, but are set to kick in. We’re keeping a close eye on it.”
My own work is on the connected initiative called Data Rights Protocol which is aimed at providing a common open source API so processing the legally required data rights requests by Consumer through the Permission Slip app can be faster, cheaper, and better. That’s at DataRightsProtocol.org I think that protocol addresses some of the questions and ideas expressed in this thread.
“Here are some alternative words or concepts that could potentially provide a more nuanced or accurate description of the phenomenon compared to solely using "confabulation":
- Imputation: Generating explanatory responses by imputing or attributing plausible details, characteristics, or causal relationships even when factually incorrect.
- Speculation: The responses reflect a type of informed speculation when direct factual knowledge is lacking, as opposed to confabulation which often implies a pathological or impaired process.
- Heuristic reasoning: The behavior emerges from the model's trained heuristic techniques for reasoning and responding rather than any psychological process like confabulation per se.
- Plausible surmise: The responses take the form of plausible but unfounded surmises put forth due to the system design and limitations rather than an intent to confabulate.
- Bridging inference: The model draws bridging or gap-filling inferences to connect related concepts or complete a response, even if factually ungrounded.
- Suppositional fabrication: The language hints more strongly that the responses are fabricated suppositions not intended to deliberately deceive but still warranting cautious interpretation.
- Educated approximation: The responses could be viewed as a kind of educated approximation or speculation given training-imposed response pressures rather than confabulation due to impairment.
Designating it as solely "confabulation" may over-attribute psychological realism without addressing countervailing technical factors.”
Personally, I thought “Suppositional fabrication” came closest. Maybe just fabrication would work.
“You raise a good point. There is no absolute certainty that the analog quantum system operated in exactly the same way as the original chemical reaction dynamics it was meant to model. Some key caveats and limitations include:
- The analog system is still an approximation, so there may be small differences in how the dynamics play out compared to the real system.
- Mapping a complex molecular system onto qubits necessarily requires simplifications and abstractions that could influence the outcomes.
- Factors like experimental errors, imperfect state preparation or measurement in the trapped ion system may introduce discrepancies.
- Important details like multi-particle interactions or higher-order effects may not be fully captured.
- Verification that the analog system exhibits the same identifying signatures or phenomena as the natural system would strengthen confidence in the analogy.
So while the researchers aim to design the quantum analog to faithfully mimic the essential physics, perfect equivalence cannot be taken for granted due to modeling approximations and technological limitations. The mapping should be validated by testing for characteristic properties before concluding the slow-motion "observations" definitively represent the original phenomenon. With improvements, analog quantum simulation could provide increasingly accurate models of chemistry.”
Is this a reasonably well grounded statement? And if so, how can anybody hope to verify the analog is exhibiting “the same identifying signatures or phenomena as the natural system” if the whole point is that we can’t observe the natural system with any precision to start with?
“ Here are some potential ways you could apply the findings from this study in your daily life:
Diet: - Eat foods rich in antioxidants and anti-inflammatory compounds like curcumin (turmeric), catechins (green tea), and anthocyanins (berries) that may help reduce inflammation.
- Consume foods rich in NAD+ precursors like nicotinamide riboside or tryptophan to potentially support mitochondrial function.
- Follow an intermittent fasting regimen, which may enhance mitochondrial health and reduce inflammation.
- Limit foods high in saturated fats, added sugars, and processed carbs that can promote inflammation.
Supplements: - Take supplements that may inhibit cGAS/STING like quercetin, curcumin, green tea extract. However, speak to your doctor first.
- Consider supplements to support mitochondria like CoQ10, nicotinamide riboside, and alpha-lipoic acid.
Lifestyle: - Exercise regularly as it can reduce inflammation, improve mitochondrial function, and stimulate brain plasticity.
- Practice stress reduction techniques like yoga and meditation which may decrease inflammatory genes.
- Get sufficient sleep since sleep deprivation can increase inflammatory cytokines.
- Challenge your brain with cognitively stimulating activities to potentially promote neuroplasticity.
- Quit smoking, as it increases inflammation and oxidative stress.
However, changes should be made cautiously and discussed with a health professional. While the study provides promising areas to target, more research is still needed to confirm effects in humans.”
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Here are a few things I noticed that could be improved on the Python cheatsheet page:
- The dictionary section is missing explanation of dict comprehensions. Dict comprehensions are an important and useful feature for constructing dictionaries in a concise way.
- In the section on modules, it would be good to mention virtual environments. Virtual environments are an important tool for Python dependency and package management.
- The examples in the Pandas section are useful, but more explanation or details could be provided on some of the core DataFrame operations like merging/joining, groupby, aggregations, etc.
- In the sections on concurrency and parallelism, async/await could be explained and demonstrated. Asyncio is commonly used for asynchronous programming in Python.
- The cheatsheet focuses mainly on built-in modules and functionality. It could be useful to also cover some widely used 3rd party libraries like NumPy, SciPy, Matplotlib, TensorFlow, etc.
- Sections on testing and debugging could be added - things like unittest, pytest, logging, debugging tools. Testing and debugging are key skills for Python developers.
- The cheatsheet is very text heavy. More visuals, diagrams, or tables could help make it more scannable and easier to navigate.
Overall it covers a lot of ground, but filling in some of those gaps would make it more comprehensive and useful as a reference. The content is excellent, just some ways it could be expanded on.
The signal has been detected since at least 1988. An asteroid belt around a sun would be dynamic and continuously changing, making it unlikely for the same 20-minute repeating pattern to persist for decades.
The bursts vary in intensity and duration, and occasionally don't happen at all within a given window. This is not consistent with a simple periodicity expected from gaps in an asteroid belt.
The repetition period of 22 minutes is very slow for an asteroid belt around a sun. Typical asteroid belts have orbital periods measured in hours to days, not minutes.
For asteroids to completely block the emission from the sun during each 20-minute gap would require an extremely large number of asteroids, far more than seen in our own solar system's asteroid belt.
The semi-randomness of the signal is difficult to explain by gaps in an asteroid belt, which would be expected to produce much more regular periodicity.
The required size and stability of such an asteroid belt, persisting for decades around a sun, is not consistent with current astrophysical models of asteroid belt dynamics.
Here are some other theories that could potentially explain GPM J1839–10:
Precessing black hole - The repeating radio bursts could be caused by a precessing black hole accreting material. The precession period of around 22 minutes could explain the observed repeating pattern. However, such slow precession is not well understood for black holes.
Colliding neutron stars - GPM J1839–10 could be two neutron stars in a binary system that collide every 22 minutes, producing the radio bursts. However, the persistence of the signal for decades is difficult to explain in this scenario.
Magnetar with fluctuating magnetosphere - A magnetar, a type of neutron star with an extremely powerful magnetic field, could have a magnetosphere that fluctuates on a timescale of around 22 minutes. This could cause repeated emitting and blocking of radio waves, producing the observed pattern. However, current magnetar models do not predict such slow fluctuations.
Interacting binary system - GPM J1839–10 could be two orbiting objects that interact every 22 minutes, disrupting material and producing the radio emission. Possibilities include a neutron star and black hole or two neutron stars. However, the required orbital period of around 22 minutes is extremely wide for a compact binary system.
Strange state of quantum chromodynamics - Some theorists have proposed exotic states of matter governed by quantum chromodynamics that could provide a source of persistent but fluctuating radio emission. However, such proposals are highly speculative at this point.
I’m interested in this approach because it seems totally compatible with current business models (avoiding some of the worst non-profit incentive and oversight snarls) while still providing funding legitimately dedicated to advance the purpose. If this works, it might be a good framework for other purposes as well.