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My first question too. What’s to stop OpenAI from “partnering with” a small startup they “definitely don’t own” and giving them the money/S tier research to monopolize this thing’s use by hitting their priority matrix correctly? Stick said company in Ghana and they can play the 3rd world card too. And if you make that impossible by sharing access easily, I doubt anybody will have enough timeshares to train a Large model. Hope I’m wrong, but I’ve become a bit cynical lately about companies not being greedy bastards

Now that's a petition I can stand for.

Democratization of LLMs and its derivatives, is in fact, the AI safe way - Counterintuitive as it may sound to the AI DEI folks.

Can we just skip some steps and collect worldwide taxes to help train a new government?

Sounds like a buy signal for $NVDA

I know about this post. It is interesting but the results here are far from conclusive. The BLOOM papers also did translation experiments and they say "... In the one-shot setting, BLOOM can, with the right prompt, perform competent translation, although it is behind dedicated (supervised) models such as M2M-100".

So let's maybe use some quantifiable measures instead of just looking at a few cherry-picked examples and claim otherwise?

>unrelated concepts are no longer equidistant from other unrelated concepts,

Are distances normally the same for all unrelated concepts in a very high dimensional space? Does this have to do with unrelated concepts having low correlation in coordinates, so random distances in each axis, and therefore on average the same distance between each pair of unrelated concepts as any other unrelated pair?

>In other words, a model without this property might havre an embedding space that isn't large enough, but you're still teaching it things and the result is that you're cramming things into your embedding space that's too small, so unrelated concepts are no longer equidistant from other unrelated concepts, implying a relationship that doesn't really exist with the result being that the language model confuses things that shouldn't be confused.

So False Nearest Neighbors?

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I made a tool that makes it a little easier to verify OCRs of hex dumps (not necessarily hex dumps, but that's what I used it for). I'm not exactly an OCR expert, and just wondering if anyone has seen any similar tools:

You feed in segmented images and labels (as produced by some OCR system) and it'll display all images sorted by their class (so for hex dumps, 0, 1, 2, ... , F), which makes it considerably easier to spot mistakes. (You can then drag and drop images that were OCR'd wrong into their correct position and press a button to regenerate and you'll get a corrected hex dump.) At the risk of sounding spammy, the tools are available at https://blog.qiqitori.com/ocr/monospace_segmentation_tool/ (for segmentation if you don't have segmented images yet) and https://blog.qiqitori.com/ocr/verification_tool/, and here's some documentation (and screenshots) on how the tools can be used: https://blog.qiqitori.com/2023/03/ocring-hex-dumps-or-other-monospace-text-and-verifying-the-result/

cont

P: I want you to act as a social media manager. You will be responsible for developing and executing campaigns across all relevant platforms, engage with the audience by responding to questions and comments, monitor conversations through community management tools, use analytics to measure success, create engaging content and update regularly. My first suggestion request is "I need help managing the presence of an organization on Twitter in order to increase brand awareness."

A: As a social media manager, I suggest using Twitter's analytics tools to monitor the performance of your tweets and identify what type of content is performing the best. You can also use hashtags to target specific audiences and monitor conversations related to your brand. Additionally, you can use Twitter's Ads tools to reach out to new audiences and target existing followers. Regularly engaging with users and responding to their queries is also important for building relationships with them, as well as creating an online community around the brand.

V: Sure, I'd be happy to help you manage your organization's presence on Twitter! Here are some steps I recommend taking to increase brand awareness:

1. Develop a content strategy: Create a plan for the types of content you want to post, including tweets, images, and videos. Consider what will be most interesting and engaging to your target audience, and make sure to vary the types of content you post.

2. Use relevant hashtags: Research and use relevant hashtags to help your tweets reach a wider audience. Be sure to also create a branded hashtag for your organization.

3. Engage with your audience: Respond to comments and messages, and engage with your followers by sharing their content and thanking them for their support.

4. Monitor conversations: Use community management tools to monitor conversations related to your industry and brand. This will help you stay on top of industry trends and identify any potential issues.

5. Use analytics: Regularly check your Twitter analytics to see what's working and what's not. Use this data to improve your content strategy and adjust your approach as needed.

6. Create engaging content: Regularly post interesting and engaging content that will appeal to your target audience. Use images and videos to make your tweets stand out, and consider using Twitter polls to create engagement.

7. Collaborate with influencers: Collaborate with influencers in your industry to help spread the word about your brand and increase your reach.

8. Run promotions and contests: Consider running promotions and contests to encourage engagement and increase brand awareness.

By following these steps and staying active on Twitter, you can increase brand awareness and build a strong presence on the platform.

P: I want you to act as a title generator for written pieces. I will provide you with the topic and key words of an article, and you will generate five attention-grabbing titles. Please keep the title concise and under 20 words, and ensure that the meaning is maintained. Replies will utilize the language type of the topic. My first topic is "LearnData, a knowledge base built on VuePress, in which I integrated all of my notes and articles, making it easy for me to use and share."

A:

1. Exploring LearnData: A Comprehensive Guide

2. Grow Your Knowledge with LearnData

3. Leverage LearnData for Easy Reference

4. Share Your Wisdom with LearnData

5. Harness the Power of LearnData

V:

1. "LearnData: A Comprehensive Knowledge Base Built on VuePress"

2. "Effortlessly Organize and Share Your Notes and Articles with LearnData"

3. "Building a Custom Knowledge Base with LearnData: A VuePress Tutorial"

4. "Maximize Learning Efficiency with LearnData, a Personalized Knowledge Base"

5. "Discover the Power of a Personal Knowledge Base with LearnData"

Pretty good. Some of the responses seem better than Alpaca, while on the shampoo one it got it wrong in the first part, but the second part was better.

So I re-did some of the prompts I tried on the Alpaca demo that was live for a brief period of time (hosted by the og team, I think 7b):

Results:

P: I want you to act as a fallacy finder. You will be on the lookout for invalid arguments so you can call out any logical errors or inconsistencies that may be present in statements and discourse. Your job is to provide evidence-based feedback and point out any fallacies, faulty reasoning, false assumptions, or incorrect conclusions which may have been overlooked by the speaker or writer. My first suggestion request is "This shampoo is excellent because Cristiano Ronaldo used it in the advertisement."

A(lpaca): This statement is an example of the celebrity endorsement fallacy. Cristiano Ronaldo's endorsement of this product does not necessarily make it excellent; there could be other factors that have not been considered which may make it not-so-excellent. Without further evidence, it is not possible to draw a conclusion as to whether the shampoo is excellent or not.

V(icuna): This statement contains a logical error known as the ad hominem fallacy, which is a type of argument that attacks the person making the argument rather than addressing the argument itself. The statement is fallacious because the effectiveness of the shampoo does not depend on the endorsement of Cristiano Ronaldo, and the statement does not provide any evidence to support the claim that the shampoo is excellent.

A more appropriate argument would be: "This shampoo is excellent because it has been tested and proven to be effective, and Cristiano Ronaldo happens to use it."

P: I want you to act as an IT Architect. I will provide some details about the functionality of an application or other digital product, and it will be your job to come up with ways to integrate it into the IT landscape. This could involve analyzing business requirements, performing a gap analysis and mapping the functionality of the new system to the existing IT landscape. Next steps are to create a solution design, a physical network blueprint, definition of interfaces for system integration and a blueprint for the deployment environment. My first request is "I need help to integrate a CMS system."

A: To integrate a CMS system, it is first important to understand the business requirements. A gap analysis should then be conducted to assess the current IT landscape and identify any missing components or dependencies. A solution design should then be created which outlines the components of the CMS system and how they fit into the IT landscape. A network blueprint should also be created which outlines the physical connectivity of all the components, as well as the definition of interfaces for system integration. Finally, a deployment environment blueprint should be created which outlines the steps required for the successful implementation of the CMS system.

V: Sure, I can help you with integrating a CMS system into your IT landscape.

To start, let's understand the business requirements for the CMS system. What are the key functionality and features that the CMS needs to provide? Who are the key stakeholders that will be using the system and what are their specific needs? Once we have a clear understanding of the business requirements, we can perform a gap analysis to identify any gaps between the current IT landscape and the desired functionality of the CMS system.

Next, we can map the functionality of the CMS system to the existing IT landscape, identifying any potential integration points or areas of overlap. This will help us to identify any changes or modifications that need to be made to existing systems in order to accommodate the new CMS system.

Once we have a clear understanding of the business requirements, gap analysis, and integration points, we can begin to design a solution architecture for the CMS system. This will involve selecting the appropriate technology stack, defining the system components, and mapping out the interfaces and data flows between the CMS system and other systems in the IT landscape.

Next, we can create a physical network blueprint, including firewall rules, load balancing, and security measures to ensure that the CMS system is secure and accessible to the appropriate users.

Finally, we can define the deployment environment, including the hardware and software requirements, and create a deployment plan to ensure a smooth and successful integration of the CMS system into the IT landscape.

P: I want you to act as a journalist. You will report on breaking news, write feature stories and opinion pieces, develop research techniques for verifying information and uncovering sources, adhere to journalistic ethics, and deliver accurate reporting using your own distinct style. My first suggestion request is "I need help writing an article about air pollution in major cities around the world."

A: Cities around the world are dealing with a major air pollution crisis. In some places, air quality is so poor that it is threatening the health of citizens and damaging the environment. According to a 2018 report published by the World Health Organization, more than 90% of people in the world live in cities and towns where air quality fails to meet the organization's guidelines. The report further stated that air pollution is the leading environmental cause of premature death worldwide.

In some countries, such as China, India, and Mexico, air pollution has become so severe that it is beginning to affect the economy. Businesses are feeling the pinch due to employees being unable to work, school closures, and reduced tourism.

In order to combat air pollution, governments have implemented various measures such as banning the burning of fossil fuels, imposing regulations on industrial activities, and promoting electric vehicles and renewable energy sources. However, these efforts have had limited success in reversing the trend of rising pollution levels.

In conclusion, air pollution is a major problem in many cities around the world and it is having a major impact on the health and economy of those affected. Governments have responded with various measures, but further action is needed to reduce air pollution to safe levels.

V: Air pollution is a major problem in many cities around the world, affecting the health and well-being of millions of people. The World Health Organization (WHO) estimates that exposure to air pollution causes more than 3 million premature deaths each year, with urban areas disproportionately affected.

The main sources of air pollution in cities include industrial and vehicle emissions, as well as domestic burning of solid fuels. These pollutants can cause a range of health problems, including respiratory diseases, heart disease, and cancer.

Some of the most polluted cities in the world include New Delhi, India; Beijing, China; and Cairo, Egypt. In these cities, air pollution levels often exceed safe limits by many times, posing a serious threat to the health of residents.

To combat air pollution, cities are implementing a variety of measures, such as promoting public transportation, encouraging the use of electric vehicles, and regulating industrial and domestic emissions. In addition, many cities are investing in clean energy technologies, such as solar and wind power, to reduce their carbon footprint and minimize the impact of air pollution.

While progress is being made in many cities, much more needs to be done to address the issue of air pollution. It is important for city governments, as well as individuals, to take action to reduce emissions and protect the air we breathe. By working together, we can create cleaner, healthier cities for future generations.

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Who will administrate access to it?

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Perfect 10, Inc. v. Amazon.com, Inc. established that it was fair use for google images to keep thumbnail sized copies of images because providing image search was transformative.

I'm not a lawyer, but thumbnails are way closer to the original than network weights, and AI image generation is arguably way more transformative than providing image search. I'd be surprised if Stability loses that suit.

So how much a100 did it take to train?

A possibly naive question of mine, but are custom "fine tuned" models, - similar to that in this post - the only way for instruction following LLMs to ingest (larger scale) new knowledge from sources which were not included in the original training set?

Let's say for example - I want to summarize some larger scientific article or a larger book (above 50-100 pages) or multiple user interview transcripts for a corporate use-case with an LLM that has a similar response quality to that of GPT-4. Due to token limitations, these can not be put into the prompt directly, if I am correct. The new ChatGPT plugins (I still do not have access to it), will not solve that either, as they can only query some external knowledge source (retrieval plugin, web plugin), but this will just result in a keyword based query and an already truncated query result ingested into the prompt. So summarizing one new comprehensive corpus beyond the token limits needs a new model trained with that added corpus into the training set? Can you provide recommendations for that, what is the most efficient way?

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So is that saying that there is a kind of linear transformation happening between some space (the reality? Our personal model?) and the embedding space? I don’t know what embedding space is and I shouldn’t be here but you are saying interesting things.

Is this because of a lack of tools to deploy Python models/functions to the edge? Also when you say user’s machine, is it a browser or a native app?

Thanks! A few follow up questions:

• do you do most of your experiments in a notebook and then manually translate it to a classic python project for code review/deployments?
• what has been the most frustrating part about the engineering platforms? Non deterministic build/compute times?
• do you use any data auditing libraries for data quality?

Are the users responsible for using a model that was badly licensed?

I gave GPT-4 a task to name 5 novel camelids and it gave me:

Guanacorn - A playful name that combines "guanaco" with "unicorn," giving it a mythical and fantastical appeal.

Vicunimbus - A name inspired by "vicuña" and "nimbus," invoking the image of a camelid that roams among the clouds.

Zephyrella - A name that combines "zephyr" (a light wind) with "llama," suggesting a graceful and ethereal creature. Dromedazzle - A name that blends "dromedary" with "dazzle," evoking a sense of wonder and awe.

Moonvicuna - A name inspired by the moon, symbolizing the beauty and serenity of the night.

Alpacalypse - A playful and imaginative name that combines "alpaca" with "apocalypse," giving it a bold and adventurous vibe.

Personally, I like Alpacalypse.

Also, I think this will replace whoever makes Pokemon names.

collectively "leading the bull" is a much more reasonable approach than trying to stop research across the planet...