How to remove the bash history from a Linux Terminal

Removing bash history in the terminal can be done in several ways, depending on whether you want to clear the current session's history, remove specific entries, or clear the entire history file.


1. Clear the current session's history:

To clear the history of commands in the currently running shell session, use:

ಕೋಡ್

history -c

This command clears the in-memory history for the current session but does not affect the ~/.bash_history file until the session exits (and even then, it will only write the current, now empty, history).

2. Remove specific entries from history:

To remove a specific command from the history, first, identify its line number using the history command. Then, use:

ಕೋಡ್

history -d <line_number>

Replace <line_number> with the actual line number of the command you wish to remove. To make this change permanent in the ~/.bash_history file, you need to write the current history to the file afterwards:

ಕೋಡ್

history -w

3. Clear the entire bash history file:

To completely clear the ~/.bash_history file, which stores your command history across sessions, you can use:

ಕೋಡ್

cat /dev/null > ~/.bash_history

This command effectively truncates the ~/.bash_history file, making it empty. For the changes to take effect immediately in the current session and in future sessions, it is also recommended to clear the current session's history:

ಕೋಡ್

history -c && cat /dev/null > ~/.bash_history

4. Temporarily disable history saving for the current session:

If you want to prevent commands from being saved to history for the current session, you can unset the HISTFILE environment variable:

ಕೋಡ್

unset HISTFILE

Commands executed after this will not be recorded in the ~/.bash_history file until a new shell session is started or HISTFILE is set again.

Free Google courses for Generative AI

 Google just launched a free learning path for Generative AI.

If you're in tech, business, or just curious, this is worth a look.

𝟏. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈:

👉 https://lnkd.in/g7eqXQ7H

↳ Explain how generative AI works

↳ Describe generative AI model types

↳ Describe generative AI applications

𝟐. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐋𝐋𝐌:

👉 https://lnkd.in/gijvaHyZ

↳ Define large language models (LLMs)

↳ Describe LLM use cases

↳ Explain prompt tuning

↳ Describe Google’s generative AI development tools

𝟑. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈:

👉 https://lnkd.in/gWSjT4Zq

↳ Identify the need for a responsible AI practice within an organization

↳ Recognize that decisions made at all stages of a project make an impact in Responsible AI

↳ Recognize that organizations can design an AI infrastructure to fit their own business needs and values

♻️ Repost this to help your network get started 

I asked Perplexity Pro which is the best laptop for ai work & macbook is not in the list !!

 Suggest the best laptop for ai model training that can be bought in Bangalore

Top Laptops for AI Model Training (2025, Bangalore)

Model Name	GPU/CPU	RAM	Key Features & Reasons to Buy	Approx. Price (INR)	Availability
ASUS ROG Zephyrus G14	AMD Ryzen 9/7, RTX 40XX series	16/32GB	Compact, powerful CPU/GPU for deep learning; reliable ventilation	1,60,000–2,10,000	Major electronics retailers[1][2]
HP Victus 15-fb3025AX	Ryzen 7, NVIDIA RTX 4050+	16/32GB	Good for large datasets and image/video tasks, gaming build for high performance	1,40,000–1,60,000	HP, Amazon, local stores[3][4]
Holoware AI Laptop	Intel Core Ultra 5/7, Intel Arc GPU	16/32GB DDR5	India’s dedicated AI laptop, optimized for ML workloads, DDR5 RAM, efficient cooling	~1,80,000+	Direct via Holoware, Bangalore[5]
HP Omen/Acer Nitro/ASUS TUF series	Ryzen 7/9, RTX 4070/4080 (NVIDIA)	16–32GB	RTX 4070+ GPUs, high TGP, suited for prolonged ML/deep learning tasks	1,70,000–2,00,000+	Amazon sale, HP/ASUS stores[2][4]
Lenovo IdeaPad Pro 5 (AI model)	Intel Core Ultra 9, Integrated AI GPU	32GB DDR5	OLED screen, advanced AI, general ML/data science (integrated GPU, less CUDA)	1,30,000–1,60,000	Lenovo exclusive/play stores[4]

---

Expert Tips for Buying an AI/ML Laptop

• GPU is critical: For local training, prefer NVIDIA RTX series (ideally 4050 or above) for CUDA compatibility with TensorFlow/PyTorch[1][2][6].
• RAM: Minimum 16GB; 32GB preferred for large models and datasets.
• Storage: NVMe SSD (512GB–1TB) for speedy data access.
• Cooling: Machines like ROG Zephyrus, HP Omen, Holoware AI offer solid cooling to prevent performance throttling during long model training[3][5].
• Linux Compatibility: Check if your chosen machine runs Ubuntu well, as many ML frameworks work best on Linux[1].
• Sales: August 2025 Amazon festivals offer major discounts on AI/GPU laptops. Visit Bangalore’s electronics markets for local deals and warranty support[4].

---

Where to Buy in Bangalore

• Physical Stores: Pai International, Croma, authorized HP/ASUS/Lenovo stores.
• Online: Amazon India (watch for sales periods like the Great Freedom Festival), dedicated sites like Holoware for India-specific AI laptops[5][4][7][8].
• Refurbished Options: EazyPC offers checked, high-spec used models at a lower price, suitable for budget-conscious AI practitioners[1].

---

Standout Recommendation

For maximum AI training power, the ASUS ROG Zephyrus G14 (with NVIDIA RTX 4060 or 4070, Ryzen 9/7, and at least 32GB RAM) is one of the best available in Bangalore for deep learning, model prototyping, and heavy ML workloads. If you want a specialized option, consider the Holoware AI laptop—designed and supported locally in India for AI workloads (though with Intel Arc GPUs, so check framework compatibility)[1][2][5][4].

---

Always confirm exact specs and CUDA compatibility if you primarily work in TensorFlow or PyTorch, and ensure the laptop fits your specific dataset and framework needs before purchase[1][2][5][9][4][6].

Sources
[1] Best Laptop For Artificial Intelligence Students 2025 https://eazypc.in/best-laptop-for-artificial-intelligence-students-in-2025/
[2] Best Laptops for AI & Machine Learning (2025) https://www.youtube.com/watch?v=_2Eie6LayZc
[3] Best HP Laptops for AI Development India 2025 https://www.hp.com/in-en/shop/tech-takes/post/best-workstations-for-ai-development
[4] AI powered laptops price drop in Amazon Great Freedom Festival … https://www.hindustantimes.com/technology/ai-powered-laptops-price-drop-in-amazon-great-freedom-festival-sale-with-up-to-48-off-on-ryzen-ai-and-core-ultra-models-101754454762242.html
[5] Top Laptop for Artificial Intelligence in India https://holoware.co/best-laptop-for-artificial-intelligence-in-india-holoware-guide/
[6] Best Laptop for Data Science in 2025: Top 15 Picks https://www.upgrad.com/blog/top-10-best-data-science-laptops/
[7] AI Laptops in India 2025 – Best AI Laptop Brands & Buying Guide https://www.paiinternational.in/blog-details/all-about-ai-laptops-what-they-are-how-they-work-w
[8] Top 5 AI Laptops in India in 2025 - April https://www.paiinternational.in/blog-details/revolutionize-your-work-play-top-5-ai-laptops-in-i
[9] Best Laptop for Machine Learning in 2025 https://www.edureka.co/blog/best-laptop-for-machine-learning/
[10] Best Affordable AI Laptops for Gaming & Studies | HP® Tech Takes https://www.hp.com/in-en/shop/tech-takes/post/affordable-ai-laptops-gaming-school-balance

why is apple MacBook not in this list

Apple MacBook models, including the MacBook Pro with Apple Silicon (M1, M2, and M3 chips), are not typically recommended for intensive AI model training—particularly for tasks using popular frameworks like TensorFlow and PyTorch—due to several key reasons relevant in 2025:

- **Lack of CUDA Support:** Most AI and machine learning libraries (especially TensorFlow and PyTorch) use NVIDIA’s CUDA platform for GPU acceleration. Apple's M-series chips use integrated graphics, which are not CUDA-compatible, meaning you can't leverage powerful GPU acceleration for many deep learning tasks as you would on an NVIDIA RTX-equipped laptop[1][2][3].

- **Limited eGPU Expansion:** Apple Silicon Macs do not natively support external graphics cards (eGPUs) for ML, unlike earlier Intel-based Macs.

- **Framework Optimization:** While Apple has made progress with Metal and CoreML optimizations, the overall ML ecosystem (especially for research and large-scale model training) still relies heavily on CUDA and NVIDIA GPUs for maximum performance with large datasets and advanced architectures[1][4][5].

- **Native Support Challenges:** Some advanced features in deep learning libraries, along with many third-party tools and dependencies, either do not work optimally or are not fully supported on Apple Silicon, especially for newest AI research tools.

- **Price-to-Performance:** For a similar budget, Windows laptops (with NVIDIA GPUs) usually offer much better raw performance for AI/ML model training compared to Apple MacBooks[1][4][3][5].

Apple MacBooks can be excellent for software development, classical machine learning (CPU-based), and on-the-go prototyping, but for **heavy AI model training**, a laptop with a high-end NVIDIA GPU remains the standard recommendation in India and globally, which is why MacBook is not included in the top picks for this specific requirement[1][4][2][3][5].

Citations:

[1] Best Laptop For Artificial Intelligence Students 2025 https://eazypc.in/best-laptop-for-artificial-intelligence-students-in-2025/

[2] Top Laptop for Artificial Intelligence in India https://holoware.co/best-laptop-for-artificial-intelligence-in-india-holoware-guide/

[3] Best Laptop for Machine Learning in 2025 https://www.edureka.co/blog/best-laptop-for-machine-learning/

[4] Best Laptops for AI & Machine Learning (2025) https://www.youtube.com/watch?v=_2Eie6LayZc

[5] Best Laptop for Data Science in 2025: Top 15 Picks https://www.upgrad.com/blog/top-10-best-data-science-laptops/

"Passwords" button stuck in the desktop in mac OS

There is an annoying "passwords" button stuck on the Mac OS desktop. Check this link out for a detailed description & probable workarounds. Pressing cmd+ left click helped me get rid of it in my case.

 https://discussions.apple.com/thread/252109550?answerId=254260694022&sortBy=rank#254260694022

AI tools for Software Engineers

 

How to configure passwordless login in Mac OS X and Linux

Overview


This article walks through configuring your website user's SSH connection to your DreamHost server so you will no longer have to enter your password.

Background

Once you set up a shell user and try to log in via SSH, you'll find you must enter your password each time. If you’d like to avoid entering your password every time, you can set up Passwordless Login. This way, you'll be able to automatically log in immediately without needing to enter your password.
How to configure passwordless login

The following instructions configure Passwordless Login for any Unix, Linux, OSX, or Cygwin machine.


In this article, username@server.dreamhost.com is used as the login example.Make sure to replace username with your actual shell username.
Make sure to replace the servername with your DreamHost servername.

Additionally, you can use the default key name of id_ed25519 or create a custom key name. Make sure you use the key name you choose in Step #3 throughout the remaining steps.

Configuring a shell user

See this article for instructions on changing your website user to an SSH (shell user) in your panel. This is required to run the SSH commands in this article.

Creating the .ssh directory on your server (DreamHost server)

This step confirms if the .ssh directory already exists on your DreamHost server, which is needed to copy your local SSH key to your server.

Log into your server via SSH and run the following commands to confirm the ~/.ssh directory exists under your username.
cd ~ ls -la | grep .ssh
If you see the .ssh directory listed, proceed with the next step.
If you do not see it, run the following command to create this directory:
mkdir ~/.ssh


Generating the key pair (home computer)

On your home computer:Open an SSH terminal.
Generate an ed25519 private key using ssh-keygen under your username:
ssh-keygen -t ed25519 Generating a public/private ed25519 key pair. Enter the file in which you wish to save they key (i.e., /Users/username/.ssh/id_ed25519):



Custom key name

If you press Enter, the key will be created with the default name of id_ed25519.

You can name this anything you like, but if you choose a custom name, you'll need to let your SSH client know about the new key name in Step #6 below. Also, if you choose to use a custom name, make sure to specify the full path to your user's .ssh directory. If you do not, the new key pair is created in the directory you're running the command. For example:
ssh-keygen -t ed25519 Generating a public/private ed25519 key pair. Enter the file in which you wish to save they key (i.e., /Users/username/.ssh/id_ed25519): /Users/username/.ssh/customkey_ed25519

Proceed through the prompts that appear.
Enter a passphrase (leave empty for no passphrase).



You do not need to enter a passphrase, but it's highly recommended as it protects your private key if compromised. If so, someone would still need your passphrase in order to unlock it. The exception to this is if you're running an automated process such as as cron job. You should then leave the password out. From ssh-copy-id:"Generally all keys used for interactive access should have a passphrase. Keys without a passphrase are useful for fully automated processes."
Press Enter to continue.
Enter same passphrase again:

Press Enter to continue.The following message appears:
Your identification has been saved in /Users/username/.ssh/custom_ed25519 Your public key has been saved in /Users/username/.ssh/custom_ed25519.pub The key fingerprint is: SHA256:7pNvrznUREXWY2r1otEwUWo40aKfZDFsUVDac3YuzrI The key's randomart image is: +--[ED25519 256]--+ | o+*+=| | X..o| | @.= +| | o #.* | | Q o @oB o| | . *.C.+ | | ..S.+ | | .o . .o | | .+..+. | +----[SHA256]-----+


Copying the public key to your DreamHost server (home computer)Run the following command to copy the public key on your local computer to DreamHost's server.
cat ~/.ssh/id_ed25519.pub | ssh username@server.dreamhost.com "cat >> ~/.ssh/authorized_keys"
This command responds with the following:
The authenticity of host 'server.dreamhost.com can't be established. ED25519 key fingerprint is SHA256:dhw3mJELPEz0i5Hzu/9lJR9FiJkK5EtiiPKAw/0zwuU. Are you sure you want to continue connecting (yes/no)? yes

Confirm the fingerprint in your panel on the SSH Keys page.
Type out the word yes to continue.
Enter your ssh username password when prompted.

The commands above create a new file named authorized_keys under your DreamHost user in the ~/.ssh directory.

Update the directory and file permissions (DreamHost server)

You must now update the permissions for the .ssh directory and authorized_keys file to further secure your keys.

Log into your server via SSH and run the following commands:
chmod 700 ~/.ssh chmod 600 ~/.ssh/authorized_keys


Adding your custom key to your ssh client (home computer)


This step is only necessary if you give your key a custom name in Step #3.1 above. You must then let your SSH client know what the new name is using ssh-agent.Run the following command to start ssh-agent. Make sure you use the backquote ` character and not a single quote – this backquote character is usually on the top left of your keyboard on the tilde ~ key:
eval `ssh-agent`

Run the following command to add your custom key.
ssh-add ~/.ssh/customkey_ed25519 Identity added: /Users/username/.ssh/customkey_ed25519

Confirm it's been added by running the following. It will respond with your private key's fingerprint.
ssh-add -l 256 SHA256:7pNvrznUREXWY2r1otEwUWo40aKfZDFsUVDac3YuzrI (ED25519)

Confirm that fingerprint by generating a fingerprint from your custom key's public file.
ssh-keygen -l -f ~/.ssh/customkey_ed25519.pub 256 SHA256:7pNvrznUREXWY2r1otEwUWo40aKfZDFsUVDac3YuzrI (ED25519)


Confirming the SSH connection (DreamHost server)

If everything is configured properly, you should now be able to access your DreamHost account through SSH without a password. Try logging in again.
ssh username@server.dreamhost.com


You should now be able to log in without using a password.
Specifying a key pair for SSH to use

By default, your client will use the identity (private key) named id_ed25519. However, if you've created more than one key, you can specify which one to use when connecting using the -i flag. For example:
ssh -i ~/.ssh/customkey_ed25519 username@server.dreamhost.com

See alsoSSH overview
SSH client software
Set up passwordless login in PuTTY
Courtesy: dreamhost.com

Google I/O 2025 summary

 Google just dropped their biggest Al updates ever during Google I/O 2025. 

Here are 13 new Al updates you can't miss:

1. Gemini Live. You can now turn on your camera, point at anything, and talk to Gemini about it in real time
2. Imagen. Google's best image model yet
3. Veo 3. The first video model with native sound generation
4. Deep Research
5. Project Astra. A JARVIS-like research prototype exploring the capabilities of a universal Al assistant
6. Google Flow. Al filmmaking tool for creators
7. Agent Mode. A new feature in the Gemini app that lets you state a goal, and Gemini will handle the steps to achieve it
8. Google Jules. Jules is an Al-powered coding assistant that can read your code, write tests, fix bugs, and update dependencies
9. Al Mode in Search. Al Mode transforms Google Search into a conversational assistant
10. Real-time speech translation in Google Meet
11. Google Beam. An Al-first video communication platform that turns 2D video streams into realistic 3D experiences
12. Gemma 3n. A new open-source Al model optimized for mobile devices
13. Try-On. Google's Virtual Try-On feature lets you upload a photo of yourself to see how clothes would look on you

What are your thoughts on this?

Free MCP model context protocol course

Worth investing time on learning the Model context protocol using a free course provided by huggingface.

 https://huggingface.co/learn/mcp-course/unit0/introduction

MCP vs RAG (Model Context Protocol vs Retrieval Augmented Generation)

RAG (Retrieval-Augmented Generation) focuses on enhancing AI responses by retrieving external data, while MCP (Model Context Protocol) standardizes how AI interacts with various data sources and tools.

Overview of RAG

Definition: RAG is an AI architecture that improves the accuracy and relevance of responses generated by large language models (LLMs) by pulling in up-to-date information from external sources, such as databases or APIs, before generating a reply.

2
Functionality: When a user submits a query, RAG retrieves relevant content from connected data sources and appends this information to the input prompt, enriching the model's context with real-world relevance. This helps reduce inaccuracies and hallucinations in AI responses by grounding them in verifiable sources.

2
Use Cases: RAG is particularly useful in scenarios where real-time data is crucial, such as customer support, news aggregation, and any application requiring current information.

3 Sources
Overview of MCP

Definition: MCP is a framework developed by Anthropic that standardizes how AI applications interact with various external data sources and tools, aiming to simplify integration and enhance functionality.

2
Functionality: MCP allows LLMs to fetch data from multiple sources, such as databases or APIs, without needing to create custom solutions for each interaction. It operates on a client-server model, where the MCP server manages the logic for data retrieval and the MCP client interfaces with the LLM.

2
Use Cases: MCP is designed for applications that require seamless integration of various tools and data sources, making it suitable for complex workflows and environments where multiple data interactions are necessary.

3 Sources
Key Differences

Scope: RAG is a specific method focused on improving the accuracy of LLM outputs by grounding them in external knowledge, while MCP is a broader protocol that standardizes interactions between AI and various data systems.

1
Data Retrieval: RAG retrieves external data each time a query is made, whereas MCP allows LLMs to access contextual memory and external data more efficiently, reducing the need for repeated data retrieval.

2
Integration: RAG requires specific setups for each data source, while MCP provides a universal framework that simplifies the integration of multiple data sources and tools into AI applications.

3 Sources
Conclusion
Both RAG and MCP play significant roles in enhancing AI capabilities, but they serve different purposes. RAG is ideal for applications needing real-time data retrieval to improve response accuracy, while MCP offers a standardized approach for integrating various tools and data sources, making it easier to build complex AI systems. Understanding these differences is crucial for developers and organizations looking to leverage AI effectively in their applications.

PostgreSQL list of commands

PostgreSQL, or Postgres, is an object-relational database management system that utilizes the SQL language. PSQL is a powerful interactive terminal for working with the PostgreSQL database. It enables users to execute queries efficiently and manage databases effectively.

Here, we highlight some of the most frequently used PSQL commands, detailing their functionalities to enhance your PostgreSQL experience.
Top PSQL Commands in PostgreSQL

Here are the top 22 PSQL commands that are frequently used when querying a PostgreSQL database:
Serial No.CommandDescription1 psql -d database -U user -W Connects to a database under a specific user
2 psql -h host -d database -U user -W Connect to a database that resides on another host
3 psql -U user -h host "dbname=db sslmode=require" Use SSL mode for the connection
4 \c dbname Switch connection to a new database
5 \l List available databases
6 \dt List available tables
7 \d table_name Describe a table such as a column, type, modifiers of columns, etc.
8 \dn List all schemes of the currently connected database
9 \df List available functions in the current database
10 \dv List available views in the current database
11 \du List all users and their assign roles
12 SELECT version(); Retrieve the current version of PostgreSQL server
13 \g Execute the last command again
14 \s Display command history
15 \s filename Save the command history to a file
16 \i filename Execute psql commands from a file
17 \? Know all available psql commands
18 \h Get help
19 \e Edit command in your own editor
20 \a Switch from aligned to non-aligned column output
21 \H Switch the output to HTML format
22 \q Exit psql shell

Additional Information:
The -d option in psql commands is used to state the database name.
The -U option specifies the database user.
The -h option indicates the host on which the database server resides.
The \h ALTER TABLE can be used to get detailed information on the ALTER TABLE statement.