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The schematic we were provided to use for troubleshooting on the final electronics lab of ET A school ;-)
12/02/2023

The schematic we were provided to use for troubleshooting on the final electronics lab of ET A school ;-)

Interesting paper.  Spoiler alert, "they haven't" ;-)To what extent have Large pre-trained Language Models (LLMs) develo...
12/02/2023

Interesting paper. Spoiler alert, "they haven't" ;-)

To what extent have Large pre-trained Language Models (LLMs) developed “emergent” capabilities for abstract ?

The defining characteristic of abstract reasoning is the ability to induce a rule or pattern from limited data or experience and to apply this rule or pattern to new, unseen situations.

We explore the abstract reasoning abilities of text-only and multimodal versions of GPT-4, using the ConceptARC benchmark [10], which is designed to evaluate robust understanding and reasoning with core-knowledge concepts. We extend the work of Moskvichev et al. [10] by evaluating GPT-4 on more deta...

Great free learning opportunity here
12/02/2023

Great free learning opportunity here

These on-demand courses, labs and videos about generative AI will help you reach your professional goals and boost your value as an employee.

A fun conversation with https://claude.aiQuestions - meAnswers - claudeWhat is the difference between an axiomatic and e...
11/28/2023

A fun conversation with
https://claude.ai

Questions - me
Answers - claude

What is the difference between an axiomatic and empirical proof?

The main differences between an axiomatic proof and an empirical proof are:

Axiomatic Proof:
- Starts from basic, self-evident logical axioms or postulates that are accepted without proof.
- Involves constructing a logical deduction using rules of inference and step-wise mathematical reasoning.
- Conclusions follow inevitably from the initial axioms.
- The truth depends on the validity of logical reasoning rather than any physical evidence.
- Examples: proofs in Euclidean geometry, number theory proofs.

Empirical Proof:
- Relies on verifying claims through observations, real-world data/measurements, or scientific experimentation.
- Conclusion is based on measurable evidence that supports or falsifies a hypothesis.
- Involves techniques like induction, repeatability, statistics, data analysis.
- Provides practical evidence under test conditions, but does not give a logical guarantee.
- Examples: physics or chemistry experiments, clinical trials, statistical surveys.

In summary, axiomatic proofs use deductive logic while empirical proofs use evidence from physical senses and experiments. Axiomatic proofs demonstrate universal mathematical truths whereas empirical proofs establish facts about the observable world.

How can an axiomatic proof be true if it is not proved empirically?

An axiomatic proof can demonstrate logical, mathematical truth without the need for empirical evidence because it relies on deduction and formal logic rather than measurable data. There are a few reasons why axiomatic proofs can establish true conclusions:

1. Sound premises - Axiomatic proofs depend on starting assumptions, axioms, that are self-evidently or nearly universally true. The conclusions logically follow if the premises are true.

2. Rigor of reasoning - Each inference step in an axiomatic proof is deductively valid following rules of logic. True conclusions are compelled if the reasoning itself is air-tight step-by-step.

3. Unchanged meanings - The symbols and terms have fixed meanings not vulnerable to experimental errors. So the argument holds as long as definitions remain consistent.

4. Abstraction - Mathematical concepts abstract away complicating physical details. So while limited in physical applicability, axiomatic proofs reveal universal logical/theoretical truths.

5. Predictability - Axiom-based proofs have successfully established mathematical facts later supported empirically, e.g. non-Euclidean geometries predicting cosmological phenomena accurately.

So axiomatic proofs reveal what logically must be true rather than what contingently happens to be true according to the quirks of the physical universe. The cost is a reduction in concrete applicability. But they provide dependable logical knowledge about abstract structures and relationships.

If axiomatic proofs reveal what logically must be true rather than what contingently happens to be true according to the quirks of the physical universe give an example?

A good example to illustrate this is the parallel postulate in geometry and its alternatives.

The classic Euclidean parallel postulate states:
Given a line and a point not on the line, exactly one parallel line can be drawn through the point that never intersects the first line.

For over 2000 years, mathematicians tried to prove this statement using Euclid’s other postulates. But this specific postulate could not be proven from the others.

Eventually, geometers realized there were self-consistent non-Euclidean alternatives possible by changing the parallel postulate. This includes:

1) Elliptic geometry - No parallel lines exist
2) Hyperbolic geometry - Multiple parallel lines can exist

These non-Euclidean systems seem counterintuitive. Physical space appears Euclidean. But the new geometries were just as logically valid from an axiomatic perspective.

Later on, Einstein’s theory of general relativity showed that spacetime is actually non-Euclidean (curved) as described by hyperbolic geometry. So our physical universe contingently exhibits non-Euclidean quirks that were revealed as possible mathematical truths long ago using only deductive logic and axioms.

So we see that starting from different primordial assumptions, alternative logical systems can be developed that do not match experimental reality. But the proofs within reveal universal mathematical truths - what logically must be true in those systems - rather than physical facts.

Explain the elliptic geometry example listed above?

Elliptic geometry is a non-Euclidean geometry that is based on the following alternative version of the parallel postulate:

"No parallel lines exist."

More specifically, elliptic geometry assumes that:

- Given any straight line L and any point A not on L, there are no lines through A that do not intersect L. All lines intersect.

To visualize how this geometry works, we can model it on the surface of a sphere:

- Consider the "lines" to be great circles on the sphere. For example, the equator, lines of longitude, etc.

- Take any two such "lines" (great circles). They will always intersect each other at two antipodal points.

- Now take one great circle line L, and any point A not on L. There exists no great circle line through A that does not intersect L.

So for spheres, all great circle "lines" intersect each other. There are no parallel lines. The points and lines obey the rules of elliptic geometry.

In this curved space, triangles have angle sums > 180 degrees. There is no concept of parallel vectors or translations as Euclidean geometry has. The mathematical deductions in this system follow a logical set of axioms and rules, revealing valid geometric truths - even if spheres don't match the large scale geometry of our physical universe.

So in summary, elliptic geometry provides an excellent example of a logical, self-consistent non-Euclidean system whose mathematical proofs reveal axiomatic truths that differ from observable reality.

Please explain the hyperbolic geometry example?

Hyperbolic geometry is a non-Euclidean geometry based on an alternative version of the parallel postulate:

"Given any line L and any point A not on L, there exist multiple distinct lines through A that are parallel to L (do not intersect)."

To visualize hyperbolic geometry, we can model it on a saddle shaped surface:

- Consider the "lines" to be geodesics (shortest paths) on the saddle surface.

- Take any two lines L and M. We can have two cases:
1) The lines intersect once
2) The lines never intersect i.e. are parallel

- Now take line L and point A not on L. There will be multiple lines through A that do not ever intersect L. These lines are parallel.

So a saddle surface geometry allows for the existence of many parallel lines. It satisfies the rules and mathematical deductions of hyperbolic geometry.

Key properties include:
- Triangles have angle sums < 180 degrees
- There exist similar figures of different sizes
- Parallel lines get further apart from each other

So hyperbolic geometry logically allows for spaces where Euclid's parallel postulate does not hold. This mathematical truth did not match physical reality at small scales. But it was later found that mass and energy can curve spacetime into a hyperbolic non-Euclidean geometry as described by Einstein's relativity theories.

So certain axiomatic mathematical systems can reveal logical possibilities that turn out to align with the quirks of our physical universe at large scales, even if they appear contrary to everyday geometry!

Could the elliptic geometry example actually have been an empirical proof by simply drawing the circles on a spherical object?

That's an insightful perspective. In a way, geometrically constructing great circles on an actual physical sphere and then directly observing their properties could serve as empirical proof for propositions in elliptic geometry.

For instance, we could:

1. Take a smooth sphere and mark intersecting great circles mimicking "lines"

2. Physically see that we cannot draw a great circle that doesn't intersect another great circle

3. Measure interior angles of constructed spherical "triangles" and observe the sums exceed 180 degrees

So by directly seeing and measuring geometric configurations on spheres according to the constructions and definitions of elliptic geometry, we could gather empirical evidence for its mathematical claims.

However, there are a couple important ways this would still fall short of a formal empirical proof:

1. It relies on a model - physical spheres just provide an interpretation to apply elliptic geometry concretely. The underlying mathematical system maintains its general axiomatic integrity independently.

2. Measurements may involve errors or approximations in practice even if the principles hold perfectly at a theoretical level.

So rather than constituting a proof itself, this process would likely complement existing formal axiomatic proofs by vividly confirming predictions and building additional intuitional understanding about non-intuitive systems of geometry. The empirical observations support the deductive theory but don't replace mathematical proof techniques in their axiomatic rigor.

Talk to Claude, an AI assistant from Anthropic

This is REALLY interesting because it provides such a good overview of how machine learning is currently being used to a...
11/28/2023

This is REALLY interesting because it provides such a good overview of how machine learning is currently being used to abstract away the problem solving procedure we refer to as thought and commonly referred (although nowhere it yet) to as AI.

In the past few days, there has been a lot of speculation about a breakthrough at OpenAI called Q-Star (Q*) which allegedly was what triggered the boardroom ...

"Ellen Fetter and Margaret Hamilton were responsible for programming the enormous 1960s-era computer that would uncover ...
11/28/2023

"Ellen Fetter and Margaret Hamilton were responsible for programming the enormous 1960s-era computer that would uncover strange attractors and other hallmarks of chaos theory."

The Hidden Heroines of Chaos
Two women programmers played a pivotal role in the birth of chaos theory. Their previously untold story illustrates the changing status of computation in science.

Two women programmers played a pivotal role in the birth of chaos theory. Their previously untold story illustrates the changing status of computation in science.

MS has really knocked it out of the park with AutoGen."AutoGen is a framework for simplifying the orchestration, optimiz...
11/26/2023

MS has really knocked it out of the park with AutoGen.

"AutoGen is a framework for simplifying the orchestration, optimization, and automation of LLM workflows. It offers customizable and conversable agents that leverage the strongest capabilities of the most advanced LLMs, like GPT-4, while addressing their limitations by integrating with humans and tools and having conversations between multiple agents via automated chat."

Microsoft researchers are introducing AutoGen, a framework for simplifying the orchestration, optimization, and automation of workflows for large language model (LLM) applications—potentially transforming and extending what LLMs can do. Learn more.

In light of the rapidly evolving landscape of technology, particularly in the domains of networking, storage, computatio...
11/08/2023

In light of the rapidly evolving landscape of technology, particularly in the domains of networking, storage, computation, blockchain, and artificial intelligence, it may appear that any technology older than six months to a year is perceived as outdated. However, it is worth noting that beneath the surface of this constant innovation, there exists a foundational infrastructure that plays a critical role in supporting all these cutting-edge technologies. To illustrate this point, consider an example from 14 years ago that still serves as the gold standard for presenting both the theory and practical engineering principles related to what was once known as Radio Frequency Interference (RFI). Over time, this concept has evolved into a more fitting term—Electromagnetic Interference, which encompasses not only wireless but also wired electronic connectivity and communication. This enduring standard serves as a testament to the lasting relevance of foundational technologies even in the face of rapid advancements in the tech industry.

Hopefully your week was productive and is winding down on a positive note.  To that end here's something for your brain ...
10/27/2023

Hopefully your week was productive and is winding down on a positive note. To that end here's something for your brain to shift gears to that's not AI or Blockchain related.

In radio communications systems design we often use something called the Smith chart which is a tool for helping us better understand the transmission of radio waves via cables (typically called feed or transmission lines) and antennas. When sending radio waves thru a medium such as a transmission line and antenna we deal with the phenomenon of reactance which can either hinder or enhance a radio waves propagation. The Smith Chart provides a visual representation of how these reactance variations affect the movement of electrical waves through different sections of a circuit. It allows us to understand and manipulate the reactance, which is crucial for managing the power that is either reflected back or transmitted forward within a circuit.

Brief video overview here:

To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/ZachStar/ . The first 200 of you will get 20% off Brilliant's a...

Here's something short, sweet, and not AI nor blockchain related. It's good to feed your brain a varied diet of interest...
10/11/2023

Here's something short, sweet, and not AI nor blockchain related. It's good to feed your brain a varied diet of interesting stuff. One of the most useful and unique uses of radio communications you've probably never heard of but our air travel industry wouldn't exist without it.

VOR, a crucial tool in aviation, helps pilots find their way even when they're up in the clouds. 🌥️✈️

📡 VOR uses radio signals transmitted from ground stations, allowing pilots to determine their position and orientation relative to these stations. It's like a giant compass in the sky! 🧭

💡 Here's how it works:
1. The ground station sends out radio waves in a 360° pattern.
2. Your plane's VOR receiver tunes into these waves.
3. By comparing the phase difference between two signals, it can tell the pilot which radial (a specific line extending out from the station) they are on.
4. Pilots use this info to navigate accurately, regardless of weather or visibility conditions.

Short vid overview:

This video explains the practical and technical principles behind VOR (VHF omnidirectional range) including the structure and use of the different components...

5G, still waiting on it to catch up to the hype
05/24/2023

5G, still waiting on it to catch up to the hype

Millimeter-wave fizzles and regulatory hurdles plague progress

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