The Future of Architecture: What You Need to Know
Architecture is a constantly evolving field, and the future of architecture is full of possibilities. Here are some of the trends that are expected to shape the future of architecture:
Sustainable architecture: As the world becomes increasingly aware of the environmental impact of buildings, sustainable architecture is becoming increasingly important. Sustainable buildings are designed to use less energy and resources, and they often use renewable energy sources.
Intelligent architecture: Intelligent architecture uses technology to create buildings that are more efficient and user-friendly. These buildings may use sensors to monitor energy usage and adjust accordingly, or they may use artificial intelligence to provide occupants with personalized services.
Adaptive architecture: Adaptive architecture is designed to respond to changes in the environment. These buildings may be able to adjust their shape or orientation to track the sun, or they may be able to collect rainwater or solar energy.
3D printing: 3D printing is already being used to create architectural models and prototypes, and it is expected to play an increasingly important role in the construction of buildings in the future. 3D printing can be used to create complex shapes and structures that would be difficult or impossible to build using traditional methods.
Virtual reality: Virtual reality (VR) is being used in architecture to allow clients to experience a building before it is even built. VR can be used to provide clients with a 360-degree view of a building, and it can also be used to simulate how light and sound will behave in a building.
These are just a few of the trends that are expected to shape the future of architecture. As technology continues to evolve, so too will the field of architecture. Architects who are able to embrace new technologies and trends will be well-positioned for success in the years to come.
The College of Architecture, MLSU is one of the leading colleges of architecture in India. The college offers a variety of undergraduate and postgraduate programs in architecture. The college's curriculum is designed to prepare students for the future of architecture by teaching them about sustainable architecture, intelligent architecture, adaptive architecture, 3D printing, and virtual reality. The college also has a strong research program that is focused on developing new technologies and techniques for architecture.
If you are interested in a career in architecture, the College of Architecture, MLSU is a great option. The college's strong curriculum and research program will prepare you for the future of architecture and give you the skills you need to succeed in this rapidly evolving field.
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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.
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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.
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📝 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.
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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.
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Smart Çelik Yapı Hakkında
Anahtar Kavramlar Analizi
Çelik Ev (Steel House): Çelik evler, uzun ömürlü ve sağlıklı yapılar olarak tanımlanır. Yangına ve neme dayanıklıdır ve 150 yıl ömre sahiptir. Galvaniz çelikten yapılır.
Tiny House: Küçük, taşınabilir evlerdir. Genellikle hızlı, kaliteli ve uzun ömürlü çözümler sunar.
Modüler Ev (Modular Home): Modüler evler, fabrikada üretilen ve yerinde monte edilen yapılardır. Taşınabilirlikleri ve modüler yapıları ile bilinir.
Prefabrik Ev (Prefabricated House): Fabrikada üretilen ve yerinde monte edilen evlerdir. Hızlı bir şekilde kurulabilir ve maliyet etkin bir çözüm sunar.
Ankara Çelik Evleri (Ankara Steel Homes): Ankara'da çelik ev ve villa modellerinin yapım aşamaları, üretim süreleri ve montaj zamanları hakkında bilgilerin bulunduğu yapılar.
Çelik Yapılar (Steel Structures): Galvaniz çelikten yapılan, yangına ve neme karşı dayanıklı uzun ömürlü yapılardır.
Özet
Bu belgede, çelik evlerin ve diğer modüler yapıların özellikleri ve avantajları ele alınmaktadır. Çelik evlerin yangın ve neme dayanıklı olduğu, 150 yıl ömre sahip olduğu ve galvaniz çelikten yapıldığı vurgulanmaktadır. Tiny House ve modüler yapılar gibi taşınabilir çözümler de hızlı, kaliteli ve uzun ömürlü olarak tanımlanmaktadır. Ayrıca, prefabrik evlerin fabrikada üretilip yerinde monte edilmesiyle hızlı ve maliyet etkin bir çözüm sunduğu belirtilmektedir. Belgede, özellikle Ankara'da çelik ev yapım süreçleri ve montaj süreçlerine dikkat çekilmektedir. Bu anahtar kavramlar, belgede belirtilen yapı türlerinin dayanıklılığı, taşınabilirliği ve ekonomikliği hakkında bilgi verir.
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Amazing Architecture: Generative AI Creates Eco-Friendly Buildings
By Daniel Reitberg
A powerful new tool called generative AI is making the future of building look greener. By looking at things like how much energy a building uses and what resources it uses, these AI models are changing the way sustainable buildings are designed. In this way, they can not only make buildings that are good for the environment, but also ones that are new and look good.
Imagine a building that gets all of its light from the sun during the day, so it doesn't need any extra lighting. Generative AI can make buildings that get the most sunlight, which means they use less power. These models can also look at wind patterns to help make natural air systems that are even better for the environment.
The cool thing about generative AI is that it can look into a huge design space. Traditional methods may limit the choices that can be made, but AI can create a huge number of options, some of which may be breakthroughs that were not expected. This makes long-term answers possible that may not have been thought of before.
Remember that generative AI isn't here to take the place of builders. Instead, it gives them the freedom to explore new design ideas and make buildings that are useful and good for the environment. AI can give architects more choices, and they can then use their knowledge to narrow down the choices and pick the most environmentally friendly and physically pleasing design for a given project. Generate AI is a strong tool that could change how we plan and construct a more environmentally friendly future.
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