Working of AI in a Nutshell

@Ai_Events

Xiaomi has launched a factory with no humans, where only robots with neural networks work

You heard that right: there isn't a single human inside. The robots assemble phones, check their quality, and even clean up after themselves. The speed is insane — one phone per second! And these machines can work around the clock without breaks.

When neural networks take over our jobs, we won't even be able to get a job at the factory.

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@Ai_Events

AI will be 100X more capable than GPT-4 by 2027, while computing costs are falling by 75-85% per year. This will TRANSFORM the world.
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@Ai_Events

سازمان بورس و اوراق بهادار با همکاری کانون کارگزاران بورس و اوراق بهادار برگزار می‌نماید:

نشست تخصصی با عنوان «کاربردهای هوش مصنوعی در بازار سرمایه ایران»

زمان برگزاری: روز یکشنبه مورخ 31 تیرماه از ساعت 15 الی 17

محل برگزاری: خیابان ولیعصر (عج)، بالاتر از خیابان بهشتی، کوچه دل‌افروز پلاک 32، سالن همایش‌های کانون کارگزارن بورس و اوراق بهادار

لینک ثبت‌نام

@Ai_Events

AI Engineers can be quite successful in this role without ever training anything.

This is how:

1/ Leveraging pre-trained LLMs: Select and tune existing LLMs for specific tasks. Don't start from scratch

2/ Prompt engineering: Craft effective prompts to optimize LLM performance without model modifications

3/ Implement Modern AI Solution Architectures: Design systems like RAG to enhance LLMs with external knowledge

Developers: The barrier to entry is lower than ever. 

Focus on the solution's VALUE and connect AI components like you were assembling Lego!
(Credits: Unknown)

@Ai_Events

We’re waiting  :)

@Ai_Events

AI drug discovery means a new generation of personalized medicines that actually work for YOU. And the potential for healthspan extending drugs this decade.
Peter H. Diamandis, MD


@Ai_Events

سلام.
دیوار توی مرداد و شهریور می‌خواد یه پروگرم استخدامی برای افراد تازه کار با پتانسیل زیاد برگزار کنه. این دوره که ظرفیتش کلاً ۵ تا ۸ نفره، دورهٔ اولش زمستون و بهار همین امسال برای Software Egineering برگزار شد و حالا قراره برای Data Science برگزار بشه. همون طوری که گفتم یه «پروگرم استخدامی‌»ه بنابراین اگه مطمئنید که نمی‌خواید کار کنید و صرفاً می‌خواید یه تجربهٔ دو ماهه به دست بیارید، به دردتون نمی‌خوره یا اگه کم‌تر از دو سال دیگه می‌خواید اپلای کنید بازم به دردتون نمی‌خوره.

اگه انگیزهٔ زیادی برای کار جدی در کنار قوی‌ترین افراد فیلدهای مختلف توسعهٔ نرم‌افزار توی یکی از پیشتازترین شرکت‌های تکنولوژی ایران دارید و تجربهٔ زیادی ندارید، این یه فرصت خیلی خوبه که به احتمال زیاد دست‌کم تا سال دیگه تکرار نمیشه.

اگه سؤال بیشتری درمورد این پروگرم دارید درخدمتم @MahMosTash.

لینک موقعیت شغلی مربوط به این پروگرم؛
B2n.ir/d02187


@Ai_Events

ChatGPT can now be integrated directly into the brain — competitors of Neuralink have embedded the popular neural network into their chip

Thanks to AI, a paralyzed man has gained the ability to communicate with his family: ChatGPT "reads" his thoughts and converts them into text, and eventually, into speech.
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@Ai_Events

OpenAI has released GPT-4o Mini

Here is an image with benchmarks, and it can be compared with Gemini Flash from Google (both on the graph are in orange tones).

The gap on the MATH dataset (mathematical tasks 🧐) is very noticeable. Some will say "breakthrough😏", while others will say "overfitted on data!". We will learn the truth from the experience of using the models!

However, the model from OpenAI is... twice as cheap! Only 15 cents per million
input tokens, and 60 cents per million output tokens — that’s VERY low.
Cheaper than GPT-3.5-Turbo by 65%!

And remember, you can cut these pennies by another 50% if you use the Batch API (where you upload a file with hundreds or thousands of requests, and it gets processed within a day; not suitable for chats, but good for various non-priority background tasks).

Unfortunately, the context remains at 128,000 tokens.
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@Ai_Events

In a recent interview, Jeff Dean, a leading researcher at Google, shared some insightful views that are relevant to both AI development and
environmental concerns. Firstly, he criticized the idea that just
scaling up AI models and datasets will lead to major breakthroughs in
AI. Instead, he suggests that a qualitative leap is necessary, the
nature of which is still unknown.

Regarding environmental concerns related to AI, Jeff Dean addressed the criticism about Google's increasing carbon footprint due to AI research. He clarified that:

- The transition to renewable energy sources is inherently incremental: new large-scale energy capacities must be built and integrated, and while energy consumption is steadily increasing, the carbon footprint can initially rise but is expected to drop sharply once new energy solutions are operational.

- AI's energy consumption is a small fraction of the total energy usage by tech giants, which is dominated by traditional services for billions of users and cloud services for businesses globally. The challenge, therefore, is not to make AI specifically "clean" in terms of energy but to improve the energy efficiency of data centers at large.
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@Ai_Events

Elon Musk tweeted that they started training on the newly built supercluster X.AI in Memphis, Tennessee.

This data center is equipped with 100,000 H100 GPUs, which is a substantial number compared to META's recently launched clusters of 24,576 GPUs each, and GPT-4 was rumored to have been trained on 25,000 cards.
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@Ai_Events

رویداد رونمایی از ابزار هوش مصنوعی دادماتولز به صورت اوپن سورس

در این رویداد ابزار NLP دادماتولز به صورت رسمی آزادرسانی شده و برنامه‌های توسعه جمعی با مشارکت دانشگاه و بخش خصوصی و حمایت‌های دولتی مطرح می‌شود.



⏳زمان:
دوشنبه ۱۵ مرداد ساعت ۱۰ الی ۱۲

📍مکان:
صندوق نوآوری و شکوفایی، سالن آمفی تئاتر

📎لینک ثبت نام:
https://evand.com/events/dadmatools


@Ai_Events

Meta AI released a new version of the Llama model today

The new version - 3.1 comes with a new model of 405B parameters and an upgrade of the previous versions - the 70B and 8B models. According to the release notes, the new model capabilities are similar to the GPT-4, GPT-4o, and Claude 3.5 Sonnet models.

Release notes: https://ai.meta.com/blog/meta-llama-3-1/

Model on Hugging Face: https://huggingface.co/meta-llama/Meta-Llama-3.1-405B


@Ai_Events

💡 The Power of AI Personas: A New Frontier in Startup Innovation

As a seasoned entrepreneur and investor, I've been closely watching the rise of AI personas in various industries. This technology, while seemingly simple, has the potential to revolutionize how businesses operate and interact with their customers and employees.

➡️ AI personas are not to be confused with fully autonomous "digital employees". Instead, they are AI-powered bots that operate on a specific algorithm, trained on relevant text data and fine-tuned for particular use cases. Despite their simplicity, these AI personas can effectively handle routine tasks and answer questions based on their training data – which is more than enough for 80% of most business needs.

➡️ The applications for this technology are vast and growing. We're seeing AI personas being used to train salespeople, filter job candidates, gather product feedback, and even create digital twins of celebrities or fictional characters. In education, they're transforming professional development by acting as 24/7 teaching assistants.

➡️ What's particularly exciting about this trend is its accessibility. With the right platform, businesses can create and customize their own AI personas without needing deep technical expertise. They simply need to upload relevant text data and adjust algorithm parameters to suit their specific needs.

This opens up a world of possibilities for startups. The key is identifying which operations in which industries could benefit from AI persona automation.

❗️ Here are some questions to consider:

— What routine tasks in your industry consume a lot of human time but don't necessarily require human creativity or emotional intelligence?

— Where in your business do you need to provide information or answer questions outside of normal working hours?

— Are there areas where you need to scale personal interactions without proportionally increasing staff?

— Could an AI persona help in training or onboarding processes?

— Is there a need in your industry for personalized, on-demand expert knowledge?

👌 For startup founders looking to capitalize on this trend, here's my advice:

— Start by deeply understanding the pain points in your target industry. The most successful AI persona applications will solve real, pressing problems.

— Consider the type of data you'll need to train your AI personas effectively. Ensure you have a strategy for ethically sourcing and managing this data.

— Focus on user experience. The most successful platforms will make it easy for non-technical users to create, train, and manage AI personas.

— Don't try to replace humans entirely. Instead, look for ways AI personas can augment and support human workers, freeing them up for higher-value tasks.

— Be prepared to iterate. As with any new technology, it may take time to find the perfect fit between AI capabilities and user needs.

➡️ AI personas represent a significant opportunity for startups. They offer a way to provide personalized, scalable services in a wide range of industries. While the technology itself is becoming more accessible, the real challenge – and opportunity – lies in identifying the most valuable applications and creating user-friendly platforms for implementation.

The startups that will succeed in this space will be those that can effectively bridge the gap between AI capabilities and real-world business needs. So, startup founders, it's time to start thinking: how could AI personas transform your industry?

#StartupInside

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@Ai_Events

Instant Intelligence is wild with Llama 3.1 8B + Groq
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@Ai_Events

Elon Musk says xAI's new supercomputer in Memphis was installed in just 19 days and will be used to train Grok 3, which is expected by December, and will be the most powerful AI in the world
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@Ai_Events

Huge announcement from Meta. Welcome Llama 3.1!

This is all you need to know about it:

The new models:
- The Meta Llama 3.1 family of multilingual large language models (LLMs) is a collection of pre-trained and instruction-tuned generative models in 8B, 70B, and 405B sizes (text in/text out).

- All models support long context length (128k) and are optimized for inference with support for grouped query attention (GQA).

- Optimized for multilingual dialogue use cases and outperform many of the available open source chat models on common industry benchmarks.

- Llama 3.1 is an auto-regressive language model with an optimized transformer architecture, using SFT and RLHF for alignment. Its core LLM architecture is the same dense structure as Llama 3 for text input and output.

- Tool use, Llama 3.1 Instruct Model (Text) is fine-tuned for tool use, enabling it to generate tool calls for search, image generation, code execution, and mathematical reasoning, and also supports zero-shot tool use.


@Ai_Events