#artificial intelligence lab

[cleveredlearning]

Clevered: Artificial Intelligence Lab for Schools and the Implications of NEP 2020

In the ever-evolving landscape of education, the integration of Artificial Intelligence (AI) has emerged as a transformative force, offering boundless opportunities for learning and innovation. With the advent of the National Education Policy (NEP) 2020, India has taken significant strides towards embracing AI in education, recognizing its potential to equip students with the skills needed for the future. In this context, the establishment of AI Coding Labs in schools stands as a pivotal initiative, poised to shape the next generation of thinkers, problem-solvers, and creators.

Understanding the Significance of AI Coding Labs:

AI Coding Labs serve as dynamic spaces where students are introduced to the fundamentals of AI and coding from an early age. These labs provide hands-on experience, fostering a deep understanding of AI technologies such as machine learning, neural networks, and natural language processing. By engaging in real-world projects and challenges, students develop critical thinking, computational thinking, and problem-solving skills essential for success in the digital age.

NEP 2020 and the Paradigm Shift in Education:

The National Education Policy (NEP) 2020 marks a paradigm shift in the Indian education system, emphasizing holistic development, flexibility, and the integration of technology. With its focus on skill-based learning and experiential education, NEP 2020 aligns seamlessly with the objectives of AI Coding Labs, providing a framework for their implementation across schools nationwide.

Key Objectives of AI Coding Labs:

Promoting Digital Literacy: AI Coding Labs play a crucial role in promoting digital literacy by familiarizing students with AI technologies and programming languages. Through hands-on activities and projects, students develop fluency in coding, enabling them to navigate the digital landscape with confidence.

Fostering Innovation: By encouraging experimentation and exploration, AI Coding Labs foster a culture of innovation among students. Through collaborative projects, students learn to apply AI concepts creatively, developing solutions to real-world problems and contributing to technological advancement.

Building Critical Skills: AI Coding Labs focus on nurturing critical skills such as problem-solving, analytical thinking, and creativity. Through interactive learning experiences, students learn to approach challenges methodically, fostering resilience and adaptability in the face of change.

Preparing for the Future: In a world increasingly shaped by AI and automation, AI Coding Labs prepare students for the jobs of tomorrow. By equipping them with in-demand skills such as coding, data analysis, and AI proficiency, these labs empower students to thrive in the digital economy.

Integrating AI Coding Labs into the Curriculum:

The successful implementation of AI Coding Labs requires a strategic approach that integrates them seamlessly into the existing curriculum. Schools must allocate dedicated resources for the establishment and maintenance of these labs, including trained educators, infrastructure, and software tools. Furthermore, collaboration with industry partners and experts can enrich the learning experience, providing students with insights into real-world applications of AI.

Impact of AI Coding Labs on Students:

The impact of AI Coding Labs extends far beyond the acquisition of technical skills. By nurturing curiosity, creativity, and collaboration, these labs cultivate a growth mindset among students, empowering them to embrace lifelong learning and adaptability. Moreover, by fostering diversity and inclusivity, AI Coding Labs ensure that all students have equal access to opportunities in the field of AI, regardless of their background or socioeconomic status.

Conclusion:

In conclusion, the establishment of Artificial Intelligence Lab for Schools represents a significant step towards realizing the vision of NEP 2020 and preparing students for the challenges and opportunities of the future. By equipping students with the skills, knowledge, and mindset needed to thrive in a digital world, AI Coding Labs empower them to become active contributors to society and drivers of technological innovation. As we embark on this transformative journey, let us embrace the potential of AI in education and pave the way for a brighter, more inclusive future for all.

[lorenzonuti]

Tolerance threshold.

[amazingdogsprints]

hello boy 🩷🩷

[dizzified]

GRGMNMGAE LYCRA AND ASSISTANT DRIVE ME FERAL Lycra was an average dog prior to being picked up and sold off to a lab, in which he was augmented and experimented on, and Assistant was implanted into him.

Assistant was far more intelligent than the scientists anticipated, and ended up being complex enough to shut down their systems temporarily and sever the connections they had so Lycra could escape, which is why they're currently on the run. Assistant is basically just rogue A.I intelligence and Lycra without her would really just be a dog with slightly strange mechanical pieces. The only reason Lycra knows what he does is because of Assistant's intellect, he's actually not that smart, especially not compared to her

Unfortunately, she is very short-tempered and often gets frustrated by his lack of wits, she claims the only reason she wants to protect him is for her own sake, because technically his life is her own. [She's actually fond of him and cares in her own way, she'd never admit it though] Tough love is her go-to, and she can be really fucking cruel sometimes, like going dormant for long periods of time because Lycra upset her and leaving him to wander on his own as punishment despite his apologies and pleas. Which normally ends up with Lycra breaking himself and Assistant coming back online to nag him about it.

[introvertbutterflydaily]

Indian education system is soo messed up. You will be studying Microbiology but the "skill enhancement course" will be artificial intelligence.

[tinaintokyo]

Chinese New Year in AI's imagination

Given the theme "Chinese New Year", ChatGPT writes a set of prompts, Midjourney generates the images (text to image), filters them, and hands them over to Pika 1.0 to turn them into dynamic videos (image to video).

[jah-dev]

[the-technocracy]

Aaaaaaaawww, poor wee thing! . . .

[mufawad]

The Revival of Islamic Golden age, Autonomous Ships, DART hits Asteroid, and other scientific events of the Week

In today's blog, you will read about the following science events of the week:

The Revival of Islamic Golden Age is being led by Arabs

Research on mice suggests hunger related to Socialization patterns

Necessity proves to be the mother of Invention again as Lions return to hunt Marine Species

After Autonomous Cars; Now we have Autonomous Ships

The Flu Virus came from Sea: Research

Asteroid hit by DART; Lost 10 Lakh Kg of Mass

Lumpy Skin Diseases that Killed 2 Lakh Cattle in India last year occurred due to Climate Change. Read More

[shiningdesignersreflections]

Chapter 1: Unknown Realm

Narrated by Ai, as the Perfect Figure.

Narrator: Nighttime in the lab and no one is about.

Narrator: A computer screen is flickering. A program called “Perfect Figure” is compiling data through the night.

Perfect Figure: Red. Blue. Yellow. Green. Black. White.

Perfect Figure: Cherry red. Sky blue. Sunflower yellow. Midnight black. Snow white.

Perfect Figure: Color selection complete... Plotting line and color blocking.

Perfect Figure: Line length and curve radius.

Perfect Figure: Combining, processing, recombining, reprocessing...

Narrator: The designs and colors change with dazzling speed on the screen.

Narrator: It pauses momentarily on images that most strongly resemble fashion designs.

Narrator: Perfect Figure assigns them a number, saves them, then continues searching for the next design.

Perfect Figure: Draw... design.

Perfect Figure: Design... clothes.

Perfect Figure: Clothe... human.

Perfect Figure: Human...

Perfect Figure: Charmonroe.

Narrator: After undergoing one final advanced optimistic unchoke, the program spits out a few words.

Chapter 2

Chapter 3

[jcmarchi]

The Big Bucks in Gen AI Investments

New Post has been published on https://thedigitalinsider.com/the-big-bucks-in-gen-ai-investments/

The Big Bucks in Gen AI Investments

Two massive strategic VC funds were announced this week.

Created Using Ideogram

Next Week in The Sequence:

Edge 433: Our series about SSM continues with the introduction of the SAMBA model and the concept and SSMs for long-context windows. We review the original SAMBA paper and Microsoft’s Task Weaver agent for analytic workloads.

Edge 434: We dive into DeepMind’s amazing GameNGen model that can simulate an entire game of Doom in real time.

You can subscribe to The Sequence below:

TheSequence is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

📝 Editorial: The Big Bucks in Gen AI Investments

Mega financing rounds are the norm in this wave of generative AI, but have you ever wondered where the money comes from? One might assume that venture capital (VC) funds are driving the massive valuations of foundation model startups. After all, firms like Thrive Capital have been active in major rounds at OpenAI. However, that assumption would be misleading. The traditional VC industry is simply too small to sustain regular rounds of tens of billions of dollars. The main source of capital for foundation model makers is coming from strategic investors, specifically the hyperscalers such as Microsoft, Google, Amazon, and NVIDIA.

This phenomenon is unique to this wave of generative AI and is based on three key factors:

The capital required to continue pushing the scaling laws of foundation models is in the hundreds of billions of dollars.

The business model for most large foundation model makers revolves around achieving AGI (Artificial General Intelligence), which, as an investment thesis, is too long-term for most VCs.

Much of that investment is used for cloud computing hours and GPU purchases, effectively returning the money to the investors themselves.

Just this week, Microsoft and BlackRock announced a massive $30 billion fund focused on AI infrastructure. The alliance combines Microsoft’s strategic view of the AI market with BlackRock’s global fundraising capabilities. This may be one of the largest tech investment funds ever raised with a single focus. Also this week, Salesforce announced plans to expand its AI venture investments to $1 billion, marking the most ambitious strategic VC initiative among SaaS providers.

The trend of strategic capital displacing financial VCs in foundation model markets is likely to accelerate as the scaling laws of these models continue to push forward. Ironically, it seems the VC industry is being disrupted by AI itself.

💎 We recommend

We’re excited to share a new FREE eBook by Galileo – Mastering RAG: a comprehensive guide for building enterprise-grade RAG systems!

Get your copy today to enjoy 200 pages of in-depth content on chunking, embeddings, reranking, hallucinations, vector databases, RAG architecture, testing, evaluation, and so much more…

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Reduce hallucinations, use advanced chunking techniques, select embedding and reranking models, choose a vector database, and much more

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🔎 ML Research

Eureka

Microsoft Research published a paper proposing a framework and methology for evaluating foundation models. Eureka supports both language and multimodal evalaution pipelines —> Read more.

Neptune

Google Research published a paper introducing Neptue, a new dataset for long-term video understanding. Neptune includes question-answering scenarios for videos up to 15 minutes long —> Read more.

GRIN

Microsoft Research published a paper detailing GRIN: GRadient-INformed MoE, a new MoE architecture that incorporates expert routing based on sparsed gradient optimizations. With just 6.6B parameters, GRIN outperforms much larger models in reasoning and math evaluations —> Read more.

Qwen2.5-Coder

Alibaba Research published the technical report for Qwen2.5-Coder. The research covers the details of 1.5B and 7B variarios trained in 5.5 trillion tokens —> Read more.

NVLM

NVIDIA Research published a paper detailing NVLM, a family of frontier-class multimodal large language models. The model seems to achieve performance comparable to GPT-4o and Llama 3.1 especially on language tasks —> Read more.

Self-Correcting LLMs

Google DeepMind published a paper outlining SCoRe, a technique for developing self-correcting LLMs using reinforcement learning. SCoRe uses data self-generated data that translate into self-correction traces which steer the model into a specific direction —> Read more.

🤖 AI Tech Releases

Opik

Comet ML open sourced Opik, a tool for monitoring and evaluating foundation models —> Read more.

SQL Console for AI Datasets

Hugging Face released a SQL console for its dataset repository —> Read more.

Gen AI for YouTube

Google DeepMind announced new gneerative AI features for YouTube creators —> Read more.

🛠 Real World AI

Jupyter Notebooks at Meta

Meta discusses the best practices and frameworks for using Jupyter notebooks in their ML infrastructure —> Read more.

ML Pipelines at Yelp

Yelp discusses the use of Cassandra and Spark in their ML pipelines —> Read more.

📡AI Radar

Digital art legend Refik Anadol unveiled a large nature model built by fine-tuning Llama.

Microsoft and BlackRock partnered to launch a massive $30 billion AI investment fund.

Black Forest Labs, the image generator behind Grok, is raising $100 m illion at $1 billion valuation.

Salesforce Ventures expands its AI investments to $1 billion.

AI video platform Runway anchored a partnership with Hollywood’s Liongates Studios.

AI coding editor Supermaven raised $12 million in a new round.

AI for meetings platform Fathom raised $17 million in new funding.

AI sales automation platform Rep.ai raised $7.5 million to boost its AI digital-twin solution.

11x.ai raised $24 million to build AI digital employees.

Chatbot Arena has a dedicated site.

OpenAI might remove its nonprofit structure after the current fundraise.

AI content platform Typeface announced two new acquisitions.

TheSequence is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

[cleveredlearning]

Transforming Education: The Power of Artificial Intelligence Labs and Certified Coding Curricula in Schools

Introduction:

In an era defined by rapid technological advancements, integrating Artificial Intelligence (AI) and Coding Labs into school curricula has become a crucial component of fostering future-ready students. Recognizing the transformative potential of these educational tools, schools are increasingly adopting AI Labs and Certified Coding Curricula to equip students with essential skills for the digital age.

The Need for AI Labs in Schools:

As the world becomes more interconnected and technology-driven, the demand for individuals skilled in AI is escalating. To meet this demand, educational institutions are establishing dedicated AI labs within their premises. These labs serve as innovative spaces where students can explore the intricacies of AI, machine learning, and data science. By engaging with real-world applications, students gain a profound understanding of AI concepts, preparing them for the evolving job market.

The Role of Coding Labs in Schools:

Coding is the language of the future, and understanding it is no longer a niche skill but a fundamental literacy. To address this, schools are incorporating Coding Labs into their curricula, providing students with hands-on experience in programming languages like Python, Java, and JavaScript. These labs foster problem-solving skills, logical thinking, and creativity, laying the foundation for future careers in technology.

Certified Curriculum for Schools:

A critical aspect of implementing AI Coding Labs in schools is the use of certified curricula. These curricula ensure that students receive structured and standardized education in AI and coding, promoting a comprehensive learning experience. Certified programs often align with industry standards, guaranteeing that students are equipped with skills that are not only relevant but also recognized globally.

Components of a Comprehensive AI Lab:

An effective AI lab for schools comprises various components designed to provide a holistic learning experience. These may include state-of-the-art hardware such as high-performance computers, GPUs, and robotics kits. Additionally, software tools and platforms like TensorFlow and PyTorch enable students to engage in practical applications, fostering a deep understanding of AI concepts.

Benefits of AI Labs for Schools:

Hands-on Learning: AI labs offer students the opportunity to engage in hands-on learning, allowing them to experiment with AI algorithms and applications in a controlled environment.

Critical Thinking: Exploring AI concepts encourages critical thinking and problem-solving skills, as students tackle real-world challenges through the application of AI principles.

Interdisciplinary Learning: AI labs facilitate interdisciplinary learning, bridging the gap between technology and other subjects. Students can apply AI in areas such as biology, physics, and economics, expanding their knowledge base.

Career Readiness: Exposure to AI labs prepares students for future careers in technology, giving them a competitive edge in a job market increasingly dominated by AI-driven solutions.

The Significance of Coding Labs in Schools:

Promoting Logical Thinking: Coding labs enhance logical thinking and reasoning skills as students learn to break down complex problems into smaller, manageable tasks.

Fostering Creativity: Coding is a creative process that allows students to express themselves through problem-solving and the development of unique solutions.

Digital Literacy: Coding labs contribute to digital literacy, ensuring that students are proficient in using technology and understand the underlying principles of software development.

Adaptability: Coding skills are transferable across various fields, making students adaptable to the evolving demands of the job market.

Certified Coding Curricula:

Certified coding curricula play a pivotal role in standardizing the learning process. They ensure that students receive a structured education, covering essential programming concepts and languages. Moreover, certified programs often include assessments and examinations, validating the students' proficiency and providing a tangible recognition of their skills.

Conclusion:

The integration of AI and Coding Labs for school, coupled with certified curricula, represents a transformative approach to education. By exposing students to cutting-edge technologies and equipping them with coding skills, schools prepare them for a future where technology is intertwined with every aspect of society. As educational institutions continue to embrace these advancements, they empower students to not only navigate the digital landscape but also contribute meaningfully to the ever-evolving world of technology.

[mehmetyildizmelbourne-blog]

Why I Believe AlphaFold 3 is a Powerful Tool for the Future of Healthcare

Insights on a groundbreaking artificial intelligence tool for health sciences research Dear science and technology readers, Thanks for subscribing to Health Science Research By Dr Mike Broadly, where I curate important public health content. A few months ago, I wrote about AlphaFold 3, a groundbreaking AI tool that helps scientists understand protein structures, which are essential for…

[marcogiovenale]

da settembre 2024 a giugno 2025: "the next real", a cura di sineglossa

THE NEXT REAL Mostre ⧫ Talk ⧫ Laboratori su Arte, Intelligenza artificiale e società settembre 2024 – giugno 2025  | Bologna a cura di Sineglossa a settembre 2024 a giugno 2025 l’organizzazione culturale Sineglossa presenta The Next Real, una rassegna di eventi su arte, intelligenza artificiale e società, diffusa in varie location della città di Bologna, da Salaborsa a Dumbo, fino al Tecnopolo…

[thursdayisbetterthanfriday]

Theseus - Life-sized magnetic mouse

Year: 1950 Creator: Claude Shannon Video: AT&T Website - (Original Bell Labs) "one of the world’s first examples of machine learning: a robotic maze-solving mouse known as Theseus. The Theseus of ancient Greek mythology navigated a minotaur’s labyrinth and escaped by following a thread he’d used to mark his path. But Shannon’s electromechanical toy was able to “remember” its path with the help of telephone relay switches.

As the film begins, Shannon’s wheeled mouse methodically explores its surroundings—a 25-square maze. Shannon tells viewers that the maze’s metal walls can be freely rearranged, so Theseus must use a small computing machine to learn the layout anew each time. But the mouse, a tiny wooden device containing a bar magnet and adorned with wire whiskers, is “far too small” to contain a computing machine, he says. Instead, the machinery is hidden beneath the floor of the maze, a series of telephone relay circuits he has repurposed to do something that they had never done before: learn." - MIT Technology Review