Hello I have rf wireless camera detector and I would know what else the tool can do

I'm currently using OpenAI's API on my website. I need to track which users are hitting the API and the associated costs. Does anyone have experience with this?

I found the OpenAI API reference, but I'm looking for detailed steps or examples to implement this, including storing and visualizing the data on a dashboard. Any help or code snippets would be greatly appreciated!

Thanks!

I'm currently using OpenAI's API on my website. I need to track which users are hitting the API and the associated costs. Does anyone have experience with this?

I found the OpenAI API reference, but I'm looking for detailed steps or examples to implement this, including storing and visualizing the data on a dashboard. Any help or code snippets would be greatly appreciated!

Thanks!

looking to hear opinions/perspectives on academics, social life, etc. um is about 10k more per year for me tuition wise than sd. Thank you!

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This is probably a very common question, and i’m sorry if it is. What are the basic math classes I should take if i plan to major in comp sci? I’m going into 12th grade in less than a month and i want to be prepared for when I choose my classes in college. I know i should definitely take calculus, but in the upcoming years, what are some classes i should be taking?

As we all know, AI is "The thing" right now, and to be honest, I want to get into it. I believe is going to be extremely necessary to learn about it for the near future. What are you guys doing to "get into it"? how should I start learning about it without me feeling like I am wasting my time learning obsolete stuff in online courses and articles?

I hope to get into UDM, Gtech, UMich, UIUC, Columbia, Brown, Cornell, or UPenn for computer science.

My ECs are alright, but I have no computer science-related awards. Other than USACO Silver(Which idt is worth putting on my app unless I was gold), I don't have anything. Are there any awards/competitions that I can go for this summer before college apps?
I'm looking for something that's not as hard as USACO Gold, but something that has decent prestige to it(A little more than USACO Silver)

I currently have no experience, my bachelors degree is in Business Admin, and I am working on CompTIA A+, Network+ and Security+. Does anyone have any further advice to to fulfill the “experience” aspect of what companies are looking for these days?

I'm looking for a classification dataset preferably with missing values that is beginner-friendly for a course project. I was wondering if anyone had any suggestions.

Would the world be any different if the Motorola 68000 architecture and Unix dominated computer science?

I’m currently about to be a senior in college with my major in Computer Science, and although I’m going into my senior year and planning on graduating in May. I feel like I still know little to nothing. Will this change when I get into the field? My programming skills seem lacking when compared to people whom have established themselves in this field and even amongst my classmates I feel inadequate. I make good grades and have been proud of accomplishing that, but I can’t help but feel terrified for my future.

Hey,

I learned most of my programming experience through TypeScript, and although I enjoy using it, I have been looking for "new ways of thinking" using other languages, mostly related to multithreading programming.

I gave a short try to languages like Rust and Go, but I haven't really enjoyed building projects in those. I appreciate what they have to offer, but apparently it wasn't enough for me (may it be a burn out? who knows).

I'll quickly share some experiences, but the tl;dr is that I just want to know what languages make you say "I have a good time doing projects using X language/framework/stack".

• Rust: Absolutely love results, pattern matching, structs, enums, it has 90% of the features I'd love to have in a programming language. My problem with it is just some weird syntax things like lifetimes, macros, etc. Also, it didn't take long before compilation times went up and it was a small project, which made me reconsider it.

• Go: So simple, so beautiful. But too simple for me. Channels, `defer`, structs, everything is so good. But I really miss having a good type system - some enums, a way to nil-check without using pointers. And this is just a quirk of mine, but using PascalCase and camelCase is the worst of both worlds.

• Ruby: I am looking more for a typed (optionally compiled?) language, but Ruby earned a place. It is surprisingly enjoyable, it gives some extra flexibility I have wished to have in JS/TS at times.

Right now, after writing this, I realize I am more willing to invest more time in Rust to learn its ugly inners - maybe I will like it, maybe not, but at least I will learn something new. Still, I am interested in reading other opinions.

Alas, thanks!

Is anyone working on a programming project, an app or website, that needs some help. It would be nice to work on it together.

Hi Reddit!

We're working on an AI project focused on psychology and need your help. Please take a few minutes to fill out our anonymous survey. Your input will greatly support our research.

https://docs.google.com/forms/d/e/1FAIpQLScNO08m81mGXeyiD3XUzKkfBDQ1-aD2mumA3rQOT8WBskCxuQ/viewform?usp=sf_link

Thank you!

If anyone can remember a list of what they put on there application, or the things they felt really improved there applications.

I was reading about how banks might implement this system where they ask their users to enter certain characters of their password (say the 2nd, 3rd, and 5th) when I found out that they might just use reversible encryption with HSM and not hashing.

What if the system encrypts AND hashes your password? They store both the hash and encrypted password, so the system can decrypt the password and prompt users to enter certain characters of their password. Then, it encrypts and hashes the entered password, and compares the hashes (with the one stored in the database).

Is this less efficient or a good alternative to the normal hashing method.

I am currently in the process of exploring computer science areas to help me decide which path I want to take for further studies after undergrad. I am looking for book recommendations that could give an overview of a single area (or multiple) of computer science at a relatively detailed level. There are many great, detailed textbooks and more general computer science overviews, such as Code by Charles Petzold. What I am trying to find are books that may fall somewhere in-between those two categories, detailed enough to give an accurate description of the field without focusing on semantics the way that a textbook would tend to. Thanks!

Hello everyone,

I've been working on an idea that I believe could significantly advance our capabilities in building highly intelligent models. I aim to create a giant expert model using a combination of MoE (Mixture of Experts), multihead attention, HRRFormer, PowerInfer2, and Node.js. Here's a detailed breakdown of my plan:

The Core Idea

1. MoE and Multihead Attention with Node.js:

   • By integrating MoE with multihead attention mechanisms in a Node.js environment, I plan to build a large-scale expert model. This setup would allow for parallel processing of multiple expert models, enhancing efficiency and scalability.

2. PowerInfer2 for Efficiency:

   • Utilizing PowerInfer2, the goal is to further reduce the number of activated experts, which will significantly improve processing speed and efficiency. This optimization is crucial for handling large-scale models.

3. Scaling from GPT-4o:

   • Based on GPT-4o, I intend to scale up the architecture from x8 to x32, activating three experts at a time and leveraging PowerInfer2. This approach aims to maximize model performance while minimizing resource consumption.

4. HRRFormer for Long Sequence Processing:

   • Implementing HRRFormer (a hybrid neural-symbolic network) to handle long sequences efficiently. HRRFormer’s ability to manage extensive sequence information will complement the multihead attention mechanism, addressing issues related to information overload in short-term memory (KV cache).

5. KV Pool for Short-Term Memory:

   • The KV cache will be transformed into a KV pool, functioning as the robot's short-term memory. This structure will facilitate freedom of behavior and behavior assessment for the robot, leveraging HRRFormer’s long sequence processing capabilities.

Performance Enhancement Calculations

• HRRFormer: 22x improvement
• PowerInfer2: 5x improvement
• Node.js: 5x improvement

This combination theoretically offers a 550x performance boost under limited computational resources. By training the model to a GPT-4o level, there’s potential for an additional 20% performance increase, due to the enhanced architecture.

Deployment and Applications

Solution 1: Edge Computing with NVIDIA Jetson Orin X

• Hardware Utilization: Deploying the expanded HRRFormer and scaled GPT-4o model on edge devices like NVIDIA Jetson Orin X. This setup aims to deliver high performance on the edge, enabling real-time applications such as personal assistants and decision-making systems for robots with minimal latency.

Solution 2: Centralized Computing Cluster

• Computational Cluster: Implementing the same combination of technologies (MoE, multihead attention, HRRFormer, PowerInfer2, Node.js) on a centralized computing cluster running a scaled-up GPT-4 model. This approach aims to unleash even greater computational power, potentially reaching 27.5 ZFLOPS. This could drive large-scale AI applications and research, pushing us closer to AGI.

Broader Impact

If successfully implemented, these approaches could bring us closer to AGI (Artificial General Intelligence). While reaching AGI requires more than just computational power, this model’s architecture could be a significant step towards that goal.

Conclusion

In summary, this plan aims to harness the combined power of MoE, multihead attention, HRRFormer, PowerInfer2, and Node.js to create extremely efficient and powerful models. The theoretical performance enhancements and practical applications make this an exciting avenue for further research and development. I look forward to any thoughts, feedback, or collaboration opportunities from the community!

Ever since I learned about designing logic circuits I wondered: Why does aranging operations in such a way works so well?

I do not understand the intuition of it. Like, why is gray code necessary? Are there alternatives to KMaps that work equally well?

Hi everyone,

I’m thinking about setting up a Moodle forum for my fellow students because our school hasn't provided anything like it. The idea is to create a centralized platform where students can access all courses and roadmaps for various fields.

To cover hosting and storage costs, I’m considering adding subscription plans. The plans will primarily be to support the platform and ensure we have enough resources to keep it running smoothly.

My main motives are:

There’s a significant lack of resources like this at our university.

It would be a great way for students to connect, share knowledge, and support each other academically.

Any suggestions or ideas will be useful. Thanks!

I’d love to hear your thoughts on this! Do you think it’s a good idea? Any suggestions or advice would be greatly appreciated.

Thanks!

I will be a computer science freshman in about 3 weeks. Honestly, what really captured my interest in this field are Computational Linguistics, Natural Language Processing, and Machine Learning, those kinds of stuff.

However, I seldom hear about these subjects from other computer science majors. All I hear about is how they are going to get high-paying jobs to become software engineers, game developers, web devs, etc. when they graduate. I've done my research and found that my interests actually take a rather unconventional route than other compsci grads. My uni also doesn't teach these subjects

Should I pursue my interests, or should I follow something a little bit 'safer'? I'm the eldest son of the family and the first to go to college, so I'm a bit worried if there is enough job opportunities out there for these fields or if it's a niche that's too hard to get into

During quarantine, I was always eager to learn new computer terms, feeling like I discovered something new with every concept I grasped in computer science. Each day started with a question, leading me on a quest for answers, and ended with new questions for the next day, creating a continuous cycle. This passion led me to choose computer science as my career path in engineering because I felt it was where I truly belonged; without it, I wouldn't know where I'd end up in life. However, I became so engrossed in computer science that I forgot about connecting with people—friends and family—to share things with.

As I entered college, I was excited and curious about how much time others spent learning about computer science like me. I believed I was fulfilling my life's purpose. But over time, I realized many of my peers had different priorities and were unfamiliar with even the basics of computer science. They may have been hesitant to explore deeper, which only motivated me to challenge myself further. However, I eventually became overconfident, thinking computer science was easy and started spending more time on movies and other distractions whenever I had free time.

By graduation, I understood that many had chosen computer science for its demand, not genuine passion. Even the mentors lacked enthusiasm in teaching. Somewhere along the way, I lost my initial joy and excitement for learning. Concepts that once seemed fascinating now felt mundane, and I found myself revisiting the same material without progress. When attempting to learn new concepts now, I often think, "I've heard this before, it's not interesting," hindering my growth.

I never expected to lose my passion like my peers. I ended up in a low-profile job with minimal salary, unsure of how I got there and lacking the confidence to pursue other opportunities. I'm in a tough phase, missing my passion deeply. Can anyone help me rediscover it and bring it back to life? If you've been in a similar situation and found a way out, please guide me—I'm eager to learn from your experience.

Hi folks, can somebody direct me to papers or sources for the latest developments in AI content detection?

I came across commercial stuff like zerogpt that does a fairly good job from testing it, and I imagine they make gpt API calls to accomplish this. I am looking to learn how people develop the tools and prompts for this and what has been working/not working so far.

Thanks!