Jaey

TRUTH|H🏀🏀P|Tech|Stocks| $TSLA| $DOGE|

[Jaey @jaeydoge]

@XSupport, @XPolicy, @XLegal, @elonmusk for your review and comments:

DOGE_TRUTH Meter (DTM): A Basic Scoring System to Chase the TRUTH Using Grok3
- Concepts by @jaeydoge; Research, Analyses, and Algorithm Development by Grok3

Abstract
DOGE_TRUTH Meter (DTM) is a scoring system designed to assess the truthfulness of individuals or entities using public data. Powered by Grok3, DTM aims to combat misinformation by providing a basic truthfulness score. This document outlines its development and approach.

Introduction
Would you rather feel good with lies or be uncomfortable with the TRUTH? In an era where free speech enables disinformation and misinformation to push personal, political, and other interests, finding truth is challenging. Yet, Grok’s ability to process historical and real-time data and verify sources offers hope. This study seeks to create a basic system to gauge whether a person or entity is truthful using publicly available information. To achieve this, DTM employs a systematic approach to analyze X accounts.

Methodology
DTM leverages Grok3 to analyze X accounts by inputting handles or names. It retrieves public posts, assesses political leanings, and calculates a Truth Score based on the credibility of linked domains. The score reflects the percentage of verified posts among those categorized. For example, analyzing "@ExampleUser" might yield:

Name and Handle: Example User (@ExampleUser)
Political Leaning: Middle
Truth Score: 75%; n = 1,000 posts

This output illustrates DTM’s ability to deliver a quick, data-driven assessment of an account’s truthfulness and political stance.

Conclusion/Summary
DTM offers a novel method to evaluate truthfulness online, providing a basic yet valuable tool in the fight against misinformation. While not perfect, it serves as a starting point, with future versions potentially refining its accuracy and depth.

Disclaimer
DTM is experimental and not a definitive measure of truth. It relies on public data and automation, which may overlook nuance. The authors are not liable for its use.
DTM is experimental and not a definitive measure of truth. It relies on public data and automation, which may overlook nuance. The authors are not liable for its use.

[Jaey @jaeydoge]

Do you remember when you joined X? I do! #MyXAnniversary

[Jaey @jaeydoge]

@facetioussoup @warriorethos Thank you to both of you for your service!

[Jaey @jaeydoge]

@facetioussoup Sending prayers for your dad. 🙏

[Jaey @jaeydoge]

@facetioussoup Thanks Liz! I'm doing well. Hope you're doing well too. You take care.

[Jaey @jaeydoge]

$MP, you've finally become a runner. NFA. #RareEarthMaterials

[Jaey @jaeydoge]

@CoachDi85 @barbarianfitco Happy Independence Day to you too, Coach!

[Jaey @jaeydoge]

Happy 4th, USA! ♥️🇺🇲

[Jaey @jaeydoge]

@blaze_mb21 Will do. Take care.👊

[Jaey @jaeydoge]

!!

[Daniel Jeffries @Dan_Jeffries1]

"If not for funding for my early work in deep learning from the National Science Foundation (NSF) and Defense Advanced Research Projects Agency (DARPA), which disburse a good deal of U.S. research funding, I would not have discovered lessons about scaling that led me to pitch starting Google Brain to scale up deep learning. I am worried that cuts to funding for basic science will lead the U.S. — and also the world — to miss out on the next set of ideas," writes Andrew Ng.

The government spends a fraction of its budget on basic research and we are about cause a chain reaction of losing down the line because of it.

Each technology is built on the back of the technologies that came before it.

If we don't get clear glass, we don't get eyeglasses, and if we don't get eyeglasses the Dutch eyeglass maker doesn't see his kids using two to magnify things and then we don't get the microscope, and if we don't get the microscope, we don't get germ theory and the marvel of modern medicine.

As James Pethokoukis writes in the Conservative Futurist:

"At the height of the 1960s Space Race, the United States spent nearly 3 percent of its economy on scientific and technological research and development.17 Of that total, about 2 percent was government funding and 1 percent business funding.

"Today, the United States spends...about 0.75 percent by government. (All the various spending bills passed during the first half of the Biden administration—the Bipartisan Infrastructure Act, the CHIPS and Science Act, the Inflation Reduction Act—didn’t change federal R&D investment that much.)

"So especially on the government side, there’s still plenty of room to dramatically ramp up spending without approaching those Apollo-era levels.

"Now there’s no such thing as a free lunch or a money tree. But America’s science and technological innovation system is about as close to having a tasty free lunch beneath a blooming money tree as you’re likely to find.

"Or think of it this way: imagine having a miracle machine where we can put in $1 and get back $5 in the form of higher standards of living, health, and worker productivity, as some economists calculate.

"Of course, the exact product of this machine is hard to predict. Think of the daisy chain of science research and commercial innovation that created Uber.

"It started with Albert Einstein’s special theory of relativity, without which we wouldn’t have the Global Positioning System.19 For GPS to work, it needs to compare extremely accurate time signals from atomic clocks on satellites. But since those satellites are moving at a high velocity compared to Earth-bound Uber app users and experience time differently, they need to be adjusted according to Einstein’s equation. And if no GPS, no Uber with its smartphone-based business model."

We invest in the future or we watch the future pass us by.

[Jaey @jaeydoge]

@blaze_mb21 All is well, my brother. Just a bit busier than usual with added responsibilities at work. Hope all is well with you. Great weekend to you and to #TeamJaey.🫂

[Jaey @jaeydoge]

@facetioussoup @ALLABOUTPAPERL1 @AmyBuboltz @blaze_mb21 @RealMaziNedum @mraline51 @DivYieldDynasty @ArbieMind @UnfoldingJapan @MYMXCRYPTO @juli_liu7 @AJ23LIVE @AdesinaMar46144 @Agunagbaegbe @tayzx77 Likewise, Liz.

[Jaey @jaeydoge]

@ChrissyLessey Happy Friday, Chrissy!

[Jaey @jaeydoge]

!!

[Andrew Ng @AndrewYNg]

I am alarmed by the proposed cuts to U.S. funding for basic research, and the impact this would have for U.S. competitiveness in AI and other areas. Funding research that is openly shared benefits the whole world, but the nation it benefits most is the one where the research is done.

If not for funding for my early work in deep learning from the National Science Foundation (NSF) and Defense Advanced Research Projects Agency (DARPA), which disburse a good deal of U.S. research funding, I would not have discovered lessons about scaling that led me to pitch starting Google Brain to scale up deep learning. I am worried that cuts to funding for basic science will lead the U.S. — and also the world — to miss out on the next set of ideas.

In fact, such funding benefits the U.S. more than any other nation. Scientific research brings the greatest benefit to the country where the work happens because (i) the new knowledge diffuses fastest within that country, and (ii) the process of doing research creates new talent for that nation.

Why does most innovation in generative AI still happen in Silicon Valley? Because two teams based in this area — Google Brain, which invented the transformer network, and OpenAI, which scaled it up — did a lot of the early work. Subsequently, team members moved to other nearby businesses, started competitors, or worked with local universities. Further, local social networks rapidly diffused the knowledge through casual coffee meetings, local conferences, and even children’s play dates, where parents of like-aged kids meet and discuss technical ideas. In this way, the knowledge spread faster within Silicon Valley than to other geographies.

In a similar vein, research done in the U.S. diffuses to others in the U.S. much faster than to other geographic areas. This is particularly true when the research is openly shared through papers and/or open source: If researchers have permission to talk about an idea, they can share much more information, such as tips and tricks for how to really make an algorithm work, more quickly. It also lets others figure out faster who can answer their questions. Diffusion of knowledge created in academic environments is especially fast. Academia tends to be completely open, and students and professors, unlike employees of many companies, have full permission to talk about their work.

Thus funding basic research in the U.S. benefits the U.S. most, and also benefits our allies. It is true that openness benefits our adversaries, too. But as a subcommittee of the U.S. House of Representatives committee on science, space, and technology points out, “... open sharing of fundamental research is [not] without risk. Rather, ... openness in research is so important to competitiveness and security that it warrants the risk that adversaries may benefit from scientific openness as well.”

Further, generative AI is evolving so rapidly that staying on the cutting edge is what’s really critical. For example, the fact that many teams can now train a model with GPT-3.5- or even GPT-4-level capability does not seem to be hurting OpenAI much, which is busy growing its business by developing the cutting-edge o4, Codex, GPT-4.1, and so on. Those who invent a technology get to commercialize it first, and in a fast-moving world, the cutting-edge technology is what’s most valuable. Some studies (link in original post, below) also show how knowledge diffuses locally much faster than globally.

China was decisively behind the U.S. in generative AI when ChatGPT was first launched in 2022. However, China’s tech ecosystem is very open internally, and this has helped it to catch up over the past two years:
- There is ample funding for open academic research in China.
- China’s businesses such as DeepSeek and Alibaba have released cutting-edge, open-weights models. This openness at the corporate level accelerates diffusion of knowledge.
- China’s labor laws make non-compete agreements (which stop an employee from jumping ship to a competitor) relatively hard to enforce, and the work culture supports significant idea sharing among employees of different companies; this has made circulation of ideas relatively efficient.

While there’s also much about China that I would not want the U.S. to emulate, the openness of its tech ecosystem has helped it accelerate.

In 1945, Vannevar Bush’s landmark report “Science, The Endless Frontier” laid down key principles for public funding of U.S. research and talent development. Those principles enabled the U.S. to dominate scientific progress for decades. U.S. federal funding for science created numerous breakthroughs that have benefited the U.S. tremendously, and also the world, while training generations of domestic scientists, as well as immigrants who likewise benefit the U.S.

The good news is that this playbook is now well known. I hope many more nations will imitate it and invest heavily in science and talent. And I hope that, having pioneered this very successful model, the U.S. will not pull back from it by enacting drastic cuts to funding scientific research.

[Original post, with links: https://t.co/JR3x4O1iVr ]

[Jaey @jaeydoge]

@facetioussoup Likewise Liz.

[Jaey @jaeydoge]

@facetioussoup Likewise Liz.

[Jaey @jaeydoge]

@lecoder @ALLABOUTPAPERL1 @AmyBuboltz @blaze_mb21 @RealMaziNedum @mraline51 @DivYieldDynasty @ArbieMind @UnfoldingJapan @MYMXCRYPTO @juli_liu7 @AJ23LIVE @AdesinaMar46144 👊

[Jaey @jaeydoge]

Wednesday Evening Round of Shoutout to Team Jaey. Be a member of #TeamJaey and Let's grow together.

@jaeydoge
@ALLABOUTPAPERL1
@AmyBuboltz
@blaze_mb21
@RealMaziNedum
@mraline51
@DivYieldDynasty
@ArbieMind
@UnfoldingJapan
@MYMXCRYPTO
@juli_liu7
@AJ23LIVE
@AdesinaMar46144
@Agunagbaegbe
@tayzx77
@ChrissyLessey
@Vegasstevo
@CoachDi85
@facetioussoup
@lecoder

https://t.co/II5NKFTAaP

[Jaey @jaeydoge]

@facetioussoup @ALLABOUTPAPERL1 @AmyBuboltz @blaze_mb21 @RealMaziNedum @mraline51 @DivYieldDynasty @ArbieMind @UnfoldingJapan @MYMXCRYPTO @juli_liu7 @AJ23LIVE @AdesinaMar46144 Thanks Liz! Have a good night.