Forwarded from Artificial Intelligence Resources TP . AI Tools . AI Updates
The book: https://deeplearningwithpython.io/chapters/
More Deep Learning Resources Here: https://t.me/airesourcestp
More Deep Learning Resources Here: https://t.me/airesourcestp
"If you automate a mess, you get an automated mess." – Rod Michael
REMOTERemote Software Engineering Jobs at Global Top Companies, January 2026, Apply Now
Hiring Companies:
* Canonical, Wikimedia Foundation, Sticker Mule, Jump, DriveSavers Data Recovery, Enveritas, Steakhouse Financial, Zora, Xapo Bank, G2i, Supabase
Apply Here:
https://tinyurl.com/2sthze9h
More Remote Tech Jobs Here👇
https://t.me/jobsourceglobal
SHARE WITH YOUR FRIENDS🥳🥳
Start small, build momentum, and keep the fire alive. One commit today is better than a hundred undone ideas. 🚀
🔆 t.me/techpsyche
🔆 t.me/techpsyche
Pricing a project:
Too low - no respect.
Too high - no reply.
Middle - still doubting.
Too low - no respect.
Too high - no reply.
Middle - still doubting.
Microsoft announces powerful new chip for AI inference
Microsoft has announced the launch of its latest AI chip, the Maia 200, a powerful silicon workhorse designed to scale AI inference workloads with greater speed and efficiency than its predecessor, the Maia 100. Built with over 100 billion transistors and delivering more than 10 petaflops of 4-bit precision alongside roughly 5 petaflops of 8-bit performance, the Maia 200 tackles the computational task of running (inference) large AI models rather than training them, a phase that has become increasingly costly for AI businesses. Microsoft positions the chip as a way to optimize inference performance, lowering operational disruptions and power use while helping run even the largest models with headroom for future growth.
The announcement highlights a broader industry trend of tech giants creating custom silicon to reduce dependence on Nvidia’s GPU offerings and compete with in-house accelerators like Google’s TPU and Amazon’s Trainium.
read more...
Microsoft has announced the launch of its latest AI chip, the Maia 200, a powerful silicon workhorse designed to scale AI inference workloads with greater speed and efficiency than its predecessor, the Maia 100. Built with over 100 billion transistors and delivering more than 10 petaflops of 4-bit precision alongside roughly 5 petaflops of 8-bit performance, the Maia 200 tackles the computational task of running (inference) large AI models rather than training them, a phase that has become increasingly costly for AI businesses. Microsoft positions the chip as a way to optimize inference performance, lowering operational disruptions and power use while helping run even the largest models with headroom for future growth.
The announcement highlights a broader industry trend of tech giants creating custom silicon to reduce dependence on Nvidia’s GPU offerings and compete with in-house accelerators like Google’s TPU and Amazon’s Trainium.
read more...
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Microsoft says the Maia 200 already powers internal workloads, including its Superintelligence team and Copilot chatbot, and has invited developers, academics, and AI labs to experiment with its software development kit to optimize workloads on the new chip.
🔆 t.me/techpsyche
🔆 t.me/techpsyche
Never wait for tommorow to fix what you are doing today! Tommorow may never come!
❤1
The greatest skill you can develop is actually doing what you know you need to do
Forwarded from SQL Resources TP
SQL vs NoSQL Databases: Quick Comparison ✅
SQL Databases
- Structured data
- Fixed schema
- Table-based storage
- Strong consistency
- Popular tools: MySQL, PostgreSQL, SQL Server, Oracle
- Best use cases: Banking systems, ERP and CRM, transaction-heavy apps, reporting and analytics
- Job roles: Data Analyst, Backend Developer, Database Engineer, BI Developer
- Hiring reality: Mandatory in enterprises, core skill for analytics roles, used in almost every company
- India salary range: Fresher (4-7 LPA), Mid-level (8-18 LPA)
- Real tasks: Write complex queries, join multiple tables, build reports, ensure data integrity
NoSQL Databases
- Semi-structured or unstructured data
- Flexible schema
- Document, key-value, or graph based
- High scalability
- Popular tools: MongoDB, Cassandra, DynamoDB, Redis
- Best use cases: Real-time apps, big data systems, IoT platforms, rapidly changing products
- Job roles: Backend Developer, Data Engineer, Cloud Engineer, Platform Engineer
- Hiring reality: Strong demand in startups, common in cloud-native systems, often paired with SQL
- India salary range: Fresher (5-8 LPA), Mid-level (10-22 LPA)
- Real tasks: Store JSON documents, handle large traffic, design scalable schemas, optimize read and write speed
Quick Comparison
- Schema: SQL (fixed), NoSQL (flexible)
- Scaling: SQL (vertical), NoSQL (horizontal)
- Consistency: SQL (strong), NoSQL (eventual)
- Queries: SQL (powerful), NoSQL (simpler)
Role-based Choice
- Data Analyst: SQL required
- Backend Developer: Both useful
- Data Engineer: SQL + NoSQL
- Startup products: NoSQL preferred
Best Career Move
- Learn SQL first
- Add NoSQL for modern systems
- Use both in real projects
Which one do you prefer?
SQL ❤️
NoSQL 👍
Both 🙏
None 😮
Best Resources to learn SQL 👇
SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)
Learn & Practice SQL (https://bit.ly/4kNb15x)
SQL interview questions: https://t.me/sqlresourcestp/94
SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)
Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)
Also try to apply what you learn through hands-on projects or challenges.
ENJOY LEARNING 👍👍
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Like this post if you need more 👍❤️
SQL Databases
- Structured data
- Fixed schema
- Table-based storage
- Strong consistency
- Popular tools: MySQL, PostgreSQL, SQL Server, Oracle
- Best use cases: Banking systems, ERP and CRM, transaction-heavy apps, reporting and analytics
- Job roles: Data Analyst, Backend Developer, Database Engineer, BI Developer
- Hiring reality: Mandatory in enterprises, core skill for analytics roles, used in almost every company
- India salary range: Fresher (4-7 LPA), Mid-level (8-18 LPA)
- Real tasks: Write complex queries, join multiple tables, build reports, ensure data integrity
NoSQL Databases
- Semi-structured or unstructured data
- Flexible schema
- Document, key-value, or graph based
- High scalability
- Popular tools: MongoDB, Cassandra, DynamoDB, Redis
- Best use cases: Real-time apps, big data systems, IoT platforms, rapidly changing products
- Job roles: Backend Developer, Data Engineer, Cloud Engineer, Platform Engineer
- Hiring reality: Strong demand in startups, common in cloud-native systems, often paired with SQL
- India salary range: Fresher (5-8 LPA), Mid-level (10-22 LPA)
- Real tasks: Store JSON documents, handle large traffic, design scalable schemas, optimize read and write speed
Quick Comparison
- Schema: SQL (fixed), NoSQL (flexible)
- Scaling: SQL (vertical), NoSQL (horizontal)
- Consistency: SQL (strong), NoSQL (eventual)
- Queries: SQL (powerful), NoSQL (simpler)
Role-based Choice
- Data Analyst: SQL required
- Backend Developer: Both useful
- Data Engineer: SQL + NoSQL
- Startup products: NoSQL preferred
Best Career Move
- Learn SQL first
- Add NoSQL for modern systems
- Use both in real projects
Which one do you prefer?
SQL ❤️
NoSQL 👍
Both 🙏
None 😮
Best Resources to learn SQL 👇
SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)
Learn & Practice SQL (https://bit.ly/4kNb15x)
SQL interview questions: https://t.me/sqlresourcestp/94
SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)
Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)
Also try to apply what you learn through hands-on projects or challenges.
ENJOY LEARNING 👍👍
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Like this post if you need more 👍❤️
REMOTERemote AI/ML Jobs at Global Top Companies, January 2026, Apply Now
Hiring Companies:
* Canonical, Nethermind, Featherless .ai, Quora, Spectrum One
Apply Here:
https://tinyurl.com/bdubapmr
More Remote Tech Jobs Here👇
https://t.me/jobsourceglobal
SHARE WITH YOUR FRIENDS🥳🥳
Don't wait for a “mood to code” instead focus on building habits that carry you even when motivation fades.
Samsung’s TriFold phone will cost $2,899
Samsung has confirmed that its new Galaxy Z TriFold smartphone will go on sale in the United States on January 30, 2026, with a hefty $2,899 price tag for the 512 GB model — making it the most expensive smartphone currently offered in the U.S. market, pricier even than a fully loaded iPhone 17 Pro Max and Samsung’s own $2,000 Galaxy Z Fold. The TriFold unfolds twice to reveal a 10-inch display, the largest ever on a Galaxy phone, and is engineered to be exceptionally thin and durable, surviving up to 200,000 folds over its lifetime.
Unlike most flagship phones, Samsung will sell the TriFold directly through its own channels — Samsung Experience Stores and Samsung.com — rather than through mobile carriers, and it will come only in black with 512 GB of storage at launch. This marks the first time a tri-fold device has been officially offered in the U.S., with competitors like Huawei’s trifold not sold locally;
🔆 t.me/techpsyche
Samsung has confirmed that its new Galaxy Z TriFold smartphone will go on sale in the United States on January 30, 2026, with a hefty $2,899 price tag for the 512 GB model — making it the most expensive smartphone currently offered in the U.S. market, pricier even than a fully loaded iPhone 17 Pro Max and Samsung’s own $2,000 Galaxy Z Fold. The TriFold unfolds twice to reveal a 10-inch display, the largest ever on a Galaxy phone, and is engineered to be exceptionally thin and durable, surviving up to 200,000 folds over its lifetime.
Unlike most flagship phones, Samsung will sell the TriFold directly through its own channels — Samsung Experience Stores and Samsung.com — rather than through mobile carriers, and it will come only in black with 512 GB of storage at launch. This marks the first time a tri-fold device has been officially offered in the U.S., with competitors like Huawei’s trifold not sold locally;
🔆 t.me/techpsyche
❤1
Apple is also rumored to be working on its first folding phone later this year.
Here’s how old these companies are:
🇨🇳 TikTok: 8 years
🇺🇸 OpenAI: 9 years
🇺🇸 Zoom: 14 years
🇺🇸 Instagram: 14 years
🇺🇸 Airbnb: 17 years
🇺🇸 Twitter / X: 19 years
🇺🇸 Facebook: 21 years
🇺🇸 Tesla: 22 years
🇺🇸 Google: 26 years
🇺🇸 Netflix: 27 years
🇺🇸 Amazon: 31 years
🇺🇸 Apple: 49 years
🇺🇸 Microsoft: 50 years
🇯🇵 Sony: 79 years
🇮🇳 Tata Motors: 80 years
🇰🇷 Samsung: 87 years
🇺🇸 Boeing: 109 years
🇩🇪 BMW: 109 years
🇺🇸 IBM: 114 years
🇮🇹 Fiat: 126 years
🇫🇷 Renault: 126 years
🇺🇸 Coca-Cola: 133 years
🇯🇵 Nintendo: 135 years
🇯🇵 Toshiba: 150 years
🇫🇮 Nokia: 160 years
🔆 t.me/techpsyche
🇨🇳 TikTok: 8 years
🇺🇸 OpenAI: 9 years
🇺🇸 Zoom: 14 years
🇺🇸 Instagram: 14 years
🇺🇸 Airbnb: 17 years
🇺🇸 Twitter / X: 19 years
🇺🇸 Facebook: 21 years
🇺🇸 Tesla: 22 years
🇺🇸 Google: 26 years
🇺🇸 Netflix: 27 years
🇺🇸 Amazon: 31 years
🇺🇸 Apple: 49 years
🇺🇸 Microsoft: 50 years
🇯🇵 Sony: 79 years
🇮🇳 Tata Motors: 80 years
🇰🇷 Samsung: 87 years
🇺🇸 Boeing: 109 years
🇩🇪 BMW: 109 years
🇺🇸 IBM: 114 years
🇮🇹 Fiat: 126 years
🇫🇷 Renault: 126 years
🇺🇸 Coca-Cola: 133 years
🇯🇵 Nintendo: 135 years
🇯🇵 Toshiba: 150 years
🇫🇮 Nokia: 160 years
🔆 t.me/techpsyche