Which Book Is Best For Cet

[Priamo Gregory]

BothGPT4o and GPT4 Turbo are terrible in comparison to GPT-4 for some things, but in other places GPT4o shares the same terrible logic as GPT-4. GPT4o has been a good supplement for most things that do not involve dealing with analysis and logic, and strict commands, but I often have to switch to GPT-4 for better responses.

Because GPT4o is cheaper and sometimes equivalent to GPT4 (which is at times also a box of rocks), I find myself switching between GPT4o and GPT4 for the same types of conversations that require different types of analysis.

GPT4o:

Yes, GPT-4 and GPT-4 Turbo use different neural networks. GPT-4 Turbo is designed to be cheaper and faster than GPT-4, although the exact differences in architecture and operation are proprietary and not disclosed by OpenAI. Both models aim to provide high-quality language generation but with different optimization focuses.

A variety of terms are used to describe people who come from, or have family roots coming from, countries in Latin America and the Caribbean. In the United States, two terms are most frequently used, sometimes interchangeably: Hispanic, and some variation of Latino, Latina, or Latinx.

According to these definitions, a person from Brazil (where Portuguese is spoken) would be considered Latino (and not Hispanic) and a person from Spain would be considered Hispanic (but not Latino). A person with Mexican ancestry could be considered both (depending on where in Mexico they came from and their own sense of identity; a person of Mayan heritage or a Colombian person whose family fought for Spanish independence might understandably bristle at a term that assumes a connection with Spain).

Terry Blas defines the differences between the two terms as follows:

In academic circles, Latino/a/x has recently become the most frequently used term, though both are still in use (even in these circumstances, the language/geography rule applies: a Hispanic Studies Department is likely to focus on language and literature, while a Latino/a Studies Department will be more likely to study the living people in or with heritage from Latin America).

Danelvis Paredes, MD

Neurology Resident

Family background (country): All my family is from the Dominican Republic. We moved to Puerto Rico when I was 3 years old, and I have been living in the U.S. for two years.

What term(s) do you prefer? Latino/Latina

Why do you feel this way? I personally preferred Latina/Latino, which makes me feel more deeply about my real roots. Because Hispanic refers to language, or anyone who has ancestors from Spain, it would include people from Equatorial Guinea, which is in Africa. For this reason, I feel Latina/Latino is more representative of where I come from. Latinx makes no sense to me, and I don't feel that it represents me. The term is trying to be more inclusive, but it loses the beauty of our culture which includes and distinguishes between females and males through our language.

ngel Romero Ruiz, MMC, CNM

Program Coordinator, Duke Population Health Management Office

Family Background: Iberian peninsula (Spain and surrounding regions) and Italy

What term(s) do you prefer? Hispanic. Otherwise, Latina/o/x, depending on gender. Using Latinx exclusively is not inclusive.

Why do you feel this way? I prefer Hispanic. Many people in academia adopted Latinx to include all Latin Americans. I have a problem with that. First, Latinx is very ugly to my ears, especially in Spanish. I also see it as a form of cultural imperialism, imposed by the English-speaking community, removing gender. For me the problem is when words from another language are used in English.

I don't know who started using Latino and Latina in English. In the American music industry, the term used for decades is the gender-neutral Latin. There is Latin jazz, Latin music, the Latin Recording Academy (which includes Spain and Portugal, by the way). I have many coworkers and friends who support the LGBTQ community but really dislike being called Latinx and prefer to be called Latinas or Latinos or hispanos.

I will note that I have begun to use Latinx more deliberately to invoke the entire Latin-American population and all variations of it, especially since it has been popularly introduced in the academy. Along the same vein, I don't recall having intentionally labeled myself as "Latin@"/"Latina/o"/"Latine" but do see each term as a very cool (con)fusion of Spanish dictum and American thought, reconstructing the gender binary present in one culture with that binary's significance in another (this is also seen in one pronunciation of Latinx, "Latin-equis," as a literal hybridization of both languages). I don't belong to just one category in particular (hence, no preference), yet I strangely feel I live the reality of all of them.

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I originally posted this article on Medium last year, but with the latest updates to ChatGPT, Google's Gemini, and Anthropic's Claude, I thought this was the time to reconsider my analysis and see how much has changed. So here is an update on how four popular large language models (LLM), OpenAI's ChatGPT, Google's Gemini (previously, Bard), Inflection's Pi, and Antrophic's Claude 2 compare to each other in terms of their functionalities.

As a reminder for those not familiar, LLM is a type of artificial intelligence (AI) model trained on large amounts of text data. LLM essentially learns how to generate human-like text by predicting which word is most likely to follow the previous one (the actual stats are way more complex than this, but you get the gist).

I have to say that I still use ChatGPT the most, maybe because it was my first experience with generative AI, so it will always be one of my favourites. However, I have to say that I am not as impressed with the latest version (not sure what exactly has changed) as I now have to overexplain to ChatGPT what I want before I can get the answer I'm looking for (that is if I get the one I'm looking for in the first place!) I previously noted that I liked that it was able to comprehend even the more obscure prompts, but this seems to be less of the case lately which I'm a bit disappointed about.

I would say that help with coding in Python is still on point, which is part of the reason why I keep using ChatGPT. Aside from coding, ChatGPT could do all sorts of other things: solve math problems, write essays on a given topic, summarise large amounts of text, generate custom advice for your problem, and more. ChatGPT can also present data in different formats, including tables, JSON, HTML, and other formats. Each chat is also automatically named (although you can change the name if you like) and stored, so you can come back to it if you want.

ChatGPT still has a relatively low rate of AI hallucinations (a fancy term for when AI presents false information as facts in its answer), at least in my experience, although I would say that other ChatBots are catching up! This does require the user to input well-designed prompts into it, but overall, I rarely notice mistakes from ChatGPT, and if I do, it usually corrects itself when I ask it to.

A way around the need for a paid version would be to use Microsoft Copilot, which I became a fan of recently. It is currently available in a preview version to Microsoft 365 users (if admin permissions allow), but you can also assess it through the Microsoft Edge browser. Copilot runs on ChatGPT 3.5 (the same version as free ChatGPT), but it is connected to the internet and can generate images using another tool from OpenAI, DALL-E 2. When using the Edge, you can use Copilot to interact with the webpage you have open in the browser. The feature I found helpful was to use Copilot to summarise the information from the PDF in a foreign language (it can't necessarily translate large files yet) and then ask follow-up questions if I don't understand something from the summary. Copilot automatically provides links to its sources of information, so you can quickly and easily fact-check it if in doubt. For now, Copilot is limited to 30 responses per conversation, although I personally never really went over this limit. Copilot will allow users to essentially use ChatGPT capabilities within Microsoft apps, which would be pretty convenient, so if you are using Microsoft 365, it might be a good idea to invest in Copilot given its seamless integration with the system.

Overall, I think Gemini is a decent option to have if you need to analyze current news, but I would definitely not rely on it for this. In other aspects, it is pretty interchangeable with ChatGPT, and at this rate, it might even become better than ChatGPT for certain use cases. I would say that if you work with Google apps a lot, Gemini integration would probably be the best option for you.

Unlike ChatGPT or Gemini, Pi is not the most proficient when it comes to helping with code or summarising data in different output formats. Pi has increased its character limit for prompts (from 1000 to 4000), but it still cannot analyze large amounts of data at once. You have most of your responses as a single long conversation, although now you can create separate threads for the responses.

I first heard about Claude from a friend and decided to give it a try, but frankly, I was not impressed with its original capabilities. The latest version, Claude 2, does, however, appear to be an improvement. Claude can still answer simple questions from a text-based prompt, but now it can also do some coding help, data summaries, and even summarise user-provided PDF files (although there is a limit on that as well). The summaries of the large amounts of data were actually better and more accurate with Claude 2 compared to ChatGPT 3.5 and Gemini, in my experience!

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