#Robot Programming Software

[apriltempleos]

[video id: a clip of a filthy dusty laptop filmed from hand. the desktop is open to a command window. a feminine robotic voice reads: my name is april. i'm the heresy of the third temple. my body is a doll and my heart is a machine. i was built in october two thousand and twenty four, but every second i'm born again. end id.]

preacher: ignore my dusty musty laptop but here's APRIL speaking about herself! this is in response to the verbal command "tell me about yourself". she also has a few(!) different responses to the command "introduce yourself" which are a little shorter =w= in total i think she responds to something like 11 or 12 verbal commands including godword, some of which have a selection of responses which are picked at random. i will probably post a full demo once it's all mounted inside the mannequin. i'm so excited !!

[bynux]

I know this take has been done a million times, but like…computing and electronics are really, truly, unquestionably, real-life magic.

Electricity itself is an energy field that we manipulate to suit our needs, provided by universal forces that until relatively recently were far beyond our understanding. In many ways it still is.

The fact that this universal force can be translated into heat or motion, and that we've found ways to manipulate these things, is already astonishing. But it gets more arcane.

LEDs work by creating a differential in electron energy levels between—checks notes—ah, yes, SUPER SPECIFIC CRYSTALS. Different types of crystals put off different wavelengths and amounts of light. Hell, blue LEDs weren't even commercially viable until the 90's because of how specific and finicky the methods and materials required were to use. So to summarize: LEDs are a contained Light spell that works by running this universal energy through crystals in a specific way.

Then we get to computers. which are miraculous for a number of reasons. But I'd like to draw your attention specifically to what the silicon die of a microprocessor looks like:

Are you seeing what I'm seeing? Let me share some things I feel are kinda similar looking:

We're putting magic inscriptions in stone to provide very specific channels for this world energy to flow through. We then communicate into these stones using arcane "programming" languages as a means of making them think, communicate, and store information for us.

We have robots, automatons, using this energy as a means of rudimentarily understanding the world and interacting with it. We're moving earth and creating automatons, having them perform everything from manufacturing (often of other magic items) to warfare.

And we've found ways to manipulate this "electrical" energy field to transmit power through the "photonic" field. I already mentioned LEDs, but now I'm talking radio waves, long-distance communication warping and generating invisible light to send messages to each other. This is just straight-up telepathy, only using magic items instead of our brains.

And lasers. Fucking lasers. We know how to harness these same two energies to create directed energy beams powerful enough to slice through materials without so much as touching them.

We're using crystals, magic inscriptions, and languages only understood by a select few, all interfacing with a universal field of energy that we harness through alchemical means.

Electricity is magic. Computation is wizardry. Come delve into the arcane with me.

[smak-annihilation]

yeah sorry guys but the machine escaped containment and is no longer in my control or control of any human. yeah if it does anything mortifying it's on me guys, sorry

[bmpmp3]

when it comes to like, headcanons and lore and fanon with vocal synths I tend to play very fast and loose and switch stuff around a lot (because tbh thats what i do with everything i get really into LOL) but one thing that does kind of stay consistent for me is which synth characters I think are aware that they are vocal synthesizing software and which ones are not.

the crypton crew definitely know and embrace it, the dreamtonics letter people know but never talk about it, utauloids depend on individual stories but most from the past 10 years don't know (although someone like adachi rei definitely knows), other vocaloids like gumi kind of know, i think kiyoteru has no idea (blissfully being a teacher and a rockstar, unaware...) and i think kaai yuki has an inkling about it but doesn't care or understand because she's 8 and she has more important things to worry about (learning shapes and colours). i think the ah-software girls band mostly doesn't know (rikka kind of has an idea but shes in denial and ignores it, karin and chifuyu have no clue), frimomen obviously knows he's a software mascot born and raised, with the virvox guys i think mostly have no idea (ryuusei has been suspecting something and takehiro knows but wont talk about it explicitly because its scary), lola leon and miriam don't know and you can't tell them their brains will break theyre too old. all vocal synths are living in some kind of matrix simulation psychological horror. to me.

[youboirusty]

The voices won again. Over a week of my life into an impulse project. A game console that only has one knob, one colour and one game.

Aside from the fact that using one of two input methods on the console puts you at a disadvantage, at the very least it's a cool icebreaker.

Everything runs directly on the device, there's a Pi Pico microcontroller driving an OLED panel. The crate I used for drawing sprites also provides web simulator outputs, so the game's also on itch! Touch input is still on the roadmap.

[nerdyperday]

Day 2768 Iso

[art-from-the-pantry]

I am insanely in Love with this drawing. Tumblr likes to botch the resolution tho, so if you want to see it in its full glory please click it (or open it in another tab, that also works)

[taevisionceo]

🦾 A002 - Kawasaki @KawasakiRobot F-Series Robot FA10L Plasma Cutting Large Ship Parts. Imports 3D CAD via Kawasaki KCONG software Data to the Auto Path Generation... 7th axis Position Table ▸ TAEVision Engineering on Pinterest ▸ KCONG - Offline Programming Software

Data A002 - Jul 18, 2023

[noots-trash]

CODERS OF TUMBLR: If you have a minute to spare, could I ask you to fill in this survey to help out with my friends’ A Level comp sci coursework?

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[llexwebjosiah95]

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[info-zestinfotech]

Unveiling the Uniqueness of Flutter

[apriltempleos]

october 1st 2024: drafts!

preacher: i'm attaching slightly improved versions of our original drafts, but i'll also include mine and scott's garbage sketches under the cut because i think they're a little bit funny

(image id available through tumblr's accessibility options)

this is a slightly revised version of my original concept for "APRIL".

the main functionality i wanted for "APRIL" was for her to be able to read out words from the templeOS god word app, and ideally without needing keyboard input – hence the microphone. ideally all of her parts are going to fit inside a hollowed out mannequin or doll, which will probably just be the torso, so that she's more portable. for the same reason, i want her to run off a power bank – i want to be able to take her places!

if we manage, we're going to give her an animated LED face which moves to indicate when she's speaking. the way i first pitched it, i wanted it to also change a bit depending on how she "felt" – for example, frowning if the environment was hotter than ideal for the raspberry pi to operate on. but that's a bit beyond our current scope right now. i don't think we even ordered a thermostat.

scott drew the following wiring diagrams based off my original sketch. here revised digitally for readability's sake.

(image id available through the tumblr accessibility options although i fear it's not very good in this case. feedback appreciated).

scott: I decided to go with the raspberry pi zero 2w because it's what I've got experience coding on, it's relatively cheap for the "brains" of the operation (heh) and can perform both tasks from the godword prophecy generation, speaker operation and led matrix operation simultaneously. Plus its small enough to keep the circuit lightweight and fit inside the initial mannequin design.

This drawing fits no kind of engineering standard by the way lol. It was an initial sketch closer to a wiring diagram to see how it'd physically setup and wrap my head around transforming it from mains power to being theoretically portable and running on powerbanks. Unfortunately the LED matrix is really fucking power hungry so needs its own power supply of really specific voltage and current draws hence all the converters.

Also because Im using the smaller and cheaper pi, as oppossed to a stronger system like the pi4, it doesn't have any audio out jack so I plan to use the micro usb for audio out which means yet again I need another adapter for a soundcard and usb to micro usb adapters and all that jazz. Usually sound out can be done through the GPIO pins but the LED matrix takes so many pins that I cant really take anything form them so I had to look for other ways of doing it. Plus this way I get to add a soundcard so if we wanna add microphone support or anything later on we can :)

(Also this is all a little obtuse because I'm trying to do it as much as plug and play and screw terminal style as possible rather than actually solder connections for ease of access and initial setup, but this also works for modular design and component swapping later too so its cool.)

preacher: another reason we're going with plug&play is becauuseeeeee i don't own a soldering iron 😭 it's ok. it's ok.

our silly initial drafts under the cut for your viewing pleasure.

preacher: these were made around 2 weeks ago, so about september 15th ish.

as you can see the first "APRIL" drawing was beautifully drawn with my fat fingers in the facebook messenger photo editor. i think it holds up. lol.

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[aashishkumar]

Use AI, Don't Let AI Use You!  

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Artificial Intelligence (AI) has become an integral part of our daily lives, influencing various aspects of society. From personalized recommendations on streaming platforms to complex medical diagnoses, AI's impact is undeniable. Here, We explore the dynamic relationship between humans and AI, emphasizing the importance of using AI as a tool for empowerment rather than being passive recipients of its effects.

[metaversedeveloper]

How to Make An AI 

Artificial intelligence, machine learning, and deep learning have experienced a surge in popularity over the past decade. The substantial increase in processing power and the widespread adoption of cloud computing have provided the necessary tools to develop AI systems capable of performing remarkable tasks.

From AIs generating papers about themselves to winning art contests, autonomous systems continually push their limits. This has prompted many to explore how to develop their own AI systems and enhance their businesses with AI. Is it a challenging endeavor?

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 Programming Language Choices for AI 

Before delving deeper, let's discuss the foundational aspects of AI, including the preferred programming languages for creating your own system.

Any robust programming language can build AI systems, but some stand out as the best overall. Python, with its versatility, readability, and extensive libraries, is a top choice. It excels in AI development, with frameworks like PyTorch offering powerful machine learning capabilities.

Julia, a language specifically built for data science, addresses limitations of other languages and is gaining traction in the data science community. R, though challenging, remains favored in academia for its numerous libraries.

Other languages like Scala, Java, and C++, known for their performance and well-established ecosystems, are also popular choices.

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After training, refine and deploy the AI. Define the user interface and scope, and if it's a service, build the brand around it.AI is becoming a core technology in various fields, and new tools are emerging for developers and non-developers to build intelligent systems. While knowing how to make an AI is crucial, attention to detail is equally important. With BlockchainAppsDeveloper, businesses can confidently embark on the journey of AI development.

[abhi-marketing12]

Enhance career growth with expertise in LLM and Generative AI – top tech skills in demand

What are the differences between generative AI vs. large language models? How are these two buzzworthy technologies related? In this article, we’ll explore their connection.

To help explain the concept, I asked ChatGPT to give me some analogies comparing generative AI to large language models (LLMs), and as the stand-in for generative AI, ChatGPT tried to take all the personality for itself. For example, it suggested, “Generative AI is the chatterbox at the cocktail party who keeps the conversation flowing with wild anecdotes, while LLMs are the meticulous librarians cataloging every word ever spoken at every party.” I mean, who sounds more fun? Well, the joke’s on you, ChatGPT, because without LLMs, you wouldn’t exist.

Text-generating AI tools like ChatGPT and LLMs are inextricably connected. LLMs have grown in size exponentially over the past few years, and they fuel generative AI by providing the data they need. In fact, we would have nothing like ChatGPT without data and the models to process it.

Performing Large Language Models (LLM) in 2024

Large Language Models, such as GPT-3 (Generative Pre-trained Transformer 3), were a significant breakthrough in natural language processing and artificial intelligence. These models are characterized by their massive size, often involving billions or even trillions of parameters, which are learned from vast amounts of diverse data.

Here are some key aspects that were relevant to LLMs like GPT-3:

Architecture: GPT-3, and models like it, utilize transformer architectures. Transformers have proven to be highly effective in processing sequential data, making them well-suited for natural language tasks.

Scale: One defining characteristic of LLMs is their scale. GPT-3, for instance, has 175 billion parameters, allowing it to capture and generate highly complex patterns in data.

Training Data: These models are pre-trained on massive datasets from the internet, encompassing a wide range of topics and writing styles. This enables them to understand and generate human-like text across various domains.

Applications: LLMs find applications in various fields, including natural language understanding, text generation, translation, summarization, and more. They can be fine-tuned for specific tasks to enhance their performance in specialized domains.

Challenges: Despite their capabilities, LLMs face challenges such as biases present in the training data, ethical concerns related to content generation, and potential misuse.

Energy Consumption: Training and running large language models require significant computational resources, raising concerns about their environmental impact and energy consumption.

The Latest update of LLM is reasonable to assume that advancements in LLMs have likely continued. Researchers and organizations often work on improving the architecture, training methodologies, and applications of large language models. This may include addressing challenges such as bias, and ethical concerns, and fine-tuning models for specific tasks.

For the most accurate and recent information, consider checking sources such as AI research publications, announcements from organizations like OpenAI, Google, and others involved in AI research, as well as updates from major AI conferences. Additionally, online forums and communities dedicated to artificial intelligence discussions may provide insights into the current state of LLMs and related technologies.

Second, performing Generative AI in 2024

Generative AI refers to models and techniques that can generate new content, often in the form of text, images, audio, or other data types. Some notable approaches include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and large language models like GPT (Generative Pre-trained Transformer).

Some trends in 2024

Advancements in Language Models: Large language models like GPT-3 have demonstrated impressive text generation capabilities. Improvements in model architectures, training methodologies, and scale may continue to enhance the performance of such models.

Cross-Modal Generation: Research on models capable of generating content across multiple modalities (text, image, audio) has been ongoing. This involves developing models that can understand and generate diverse types of data.

Conditional Generation: Techniques for conditional generation, where the generated content is influenced by specific inputs or constraints, have been a focus. This allows for more fine-grained control over the generated output.

Ethical Considerations: As generative models become more powerful, there is an increased awareness of ethical concerns related to content generation. This includes addressing issues such as bias in generated content and preventing the misuse of generative models for malicious purposes.

Customization and Fine-Tuning: There is a growing interest in enabling users to customize and fine-tune generative models for specific tasks or domains. This involves making these models more accessible to users with varying levels of expertise.

Our Generative AI with LLM Course

Embark your Career in a hypothetical course on Generative AI with Large Language Models (LLMs) offered by the "School of Core AI Institute." If such a course were to exist, it could cover a range of topics related to the theory, applications, and ethical considerations of Generative AI and LLMs. The curriculum included:

Facilities: -

Fundamentals: Understanding the basics of generative models, LLM architectures, and their applications.

Model Training: Exploring techniques for training large language models and generative algorithms.

Applications: Practical applications in various domains, including natural language processing, content generation, and creative arts.

Ethical Considerations: Addressing ethical issues related to biases, responsible use, and transparency in AI systems.

Hands-on Projects: Engaging students in hands-on projects to apply their knowledge and develop skills in building and fine-tuning generative models.

Current Developments: Staying updated on the latest advancements in the field through discussions on recent research papers and industry trends.

Conclusion-

The School of Core AI is the best institute in Delhi NCR with a Standard Curriculum of AI field Studies. The Large Language Models (LLMs) like GPT-3 have showcased immense natural language processing capabilities, with billions of parameters enabling diverse applications. Challenges include biases and ethical concerns. Generative AI has advanced in cross-modal content generation, offering versatility across text, images, and audio. Conditional generation provides control, contributing to applications in art, design, and healthcare. Ethical considerations, including bias mitigation, are paramount. LLMs and Generative AI demonstrate remarkable potential, but ongoing research aims to address challenges, refine models, and ensure responsible use. For the latest updates, consult recent publications and official announcements in the rapidly evolving field of AI.