SoftBank is on the verge of finalizing a *$40 billion investment in OpenAI,* pushing its valuation to $300 billion, according to sources. This deal will make SoftBank the largest backer of OpenAI, overtaking Microsoft, which had previously led investments in the AI powerhouse. The funding will be distributed over the next 12 to 24 months, with the first tranche expected as early as spring.

A significant portion of the investment is earmarked for Stargate, an ambitious AI infrastructure project backed by OpenAI, Oracle, and SoftBank, announced by Donald Trump earlier this year. The initiative aims to strengthen U.S. AI capabilities, injecting billions into AI research and deployment.

OpenAI, under the leadership of Sam Altman, remains at the forefront of the generative AI revolution, competing with industry giants such as Elon Musk’s xAI, Google, Amazon, Meta, and Anthropic. The company continues to expand its reach with strategic partnerships, this high-stakes investment signals a new era of AI dominance.

🖥 OpenAI will develop Al-specific hardware, CEO Sam Altman says

OpenAI CEO Sam Altman revealed plans to develop AI-specific hardware and custom semiconductors, marking a major shift in tech. The company aims to collaborate with former Apple design chief Jony Ive to create new AI-focused devices, believing AI will transform human-computer interaction.

OpenAI is also working on its own chips, joining tech giants like Apple, Google, and Amazon in optimizing AI performance. However, the first prototype is expected to take several years, with voice interaction being a key feature, similar to how the iPhone revolutionized user interfaces with touchscreens.

🚨 OpenAI introduces ChatGPT Gov

OpenAI has launched ChatGPT Gov, a version of its ChatGPT platform designed for U.S. government agencies to improve efficiency and productivity. This specialized platform allows agencies to securely access advanced models like GPT-4o within their Microsoft Azure environments, ensuring compliance with security and privacy standards.

Key features include the ability to save and share conversations, upload files, create custom GPTs, and manage IT through an administrative console. Since 2024, over 90,000 users from more than 3,500 government agencies have utilized ChatGPT for tasks such as enhancing access to resources and supporting AI education. Notable users include the Air Force Research Laboratory and Los Alamos National Laboratory.

OpenAI is also pursuing FedRAMP Moderate and High accreditations for ChatGPT Enterprise and is exploring expansion into Azure’s classified regions, emphasizing its commitment to responsible AI use in government.

Here are 25 most common ML interview screening questions for each category:


1. Machine Learning fundamentals:
- Explain the difference between supervised, unsupervised, and reinforcement learning. Provide an example for each.
- What is the bias-variance tradeoff? How does it affect model performance?
- Describe the process of cross-validation. Why is it important in model evaluation?
- What is overfitting, and how can you prevent it in your models?
- Explain the concept of ensemble learning. What are bagging and boosting?

2. Statistics and Probability:
- Explain the difference between frequentist and Bayesian approaches in statistics.
- What is the Central Limit Theorem, and why is it important in machine learning?
- Describe the concept of hypothesis testing and its application in A/B testing.
- What is maximum likelihood estimation? Provide an example of its use in machine learning.
- Explain the difference between correlation and causation. How does this impact model interpretation?

3. Model Evaluation and Deployment:
- What metrics would you use to evaluate a classification model? How do they differ for balanced vs. imbalanced datasets?
- Describe the process of deploying a machine learning model in a production environment.
- What is A/B testing in the context of machine learning models? How would you design an A/B test?
- Explain the concept of model drift. How can it be detected and mitigated?
- What are the key considerations when scaling a machine learning system to handle large amounts of data or traffic?

4. Python for Machine Learning:
- How would you handle missing data in a pandas DataFrame?
- Explain the difference between a list and a numpy array in Python. When would you use one over the other?
- What are lambda functions in Python? Provide an example of how they can be used in data processing.
- Describe the purpose of the scikit-learn library. How would you use it to implement a simple classification model?
- What is the difference between *args and **kwargs in Python? How might they be useful in creating flexible ML functions?

5. Data Preprocessing:
- What is feature scaling, and why is it important? Describe different methods of feature scaling.
- How do you handle categorical variables in machine learning models? Explain one-hot encoding and label encoding.
- What is dimensionality reduction? Describe PCA (Principal Component Analysis) and its applications.
- How do you deal with imbalanced datasets? Discuss various techniques to address this issue.
- What is feature selection? Describe a few methods for selecting the most important features for a model.

So accurate

This is a class from Harvard University:

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It's free. You should be familiar with Python to take this course.

The course is for beginners. It's for those who want to build a fundamental understanding of machine learning and artificial intelligence.

It covers some of these topics:

• Generalization and overfitting
• Model building, regularization, and evaluation
• Linear and logistic regression models
• k-Nearest Neighbor
• Scikit-Learn, NumPy, Pandas, and Matplotlib

Link: https://pll.harvard.edu/course/introduction-data-science-python

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Forget Midjourney, It costs $8/M to use.

Here are 5 alternatives to you use

1. Bing Image Creator :

Simply type your ideas into Bing which will create one-of-a-kind images from text.

Platforms: Web, Android, iOS

2. Lexica

It acts as a search engine for Stable Diffusion-generated images.

Features:

- Generate 100 images per month for free.

- Effortless to use

Platform: Web

3. Stable Diffusion

It is a free and open-source model.

- Powerful capabilities

- Trained on large dataset

Platforms: Web

4. Adobe Firefly

- In-house text-to-image model by Adobe.

- Has promising features like image expansion and sketch-to-image.

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Platforms: Web

5. Playground AI

- Generate 1000 images per day for free.

- Stable Diffusion and DALL·E are available.

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Junior developers are gaining less knowledge because of ChatGPT; it's better to use ChatGPT when you know you can write the code for that feature.

You can use ChatGPT to make money online.

Here are 10 prompts by ChatGPT

1. Develop Email Newsletters:

Make interesting email newsletters to keep audience updated and engaged.

Prompt→ "I run a local community news website. Can you help me create a weekly email newsletter that highlights key local events, stories, and updates in a compelling way?"

2. Create Online Course Material:

Make detailed and educational online course content.

Prompt→ "I'm creating an online course about basic programming for beginners. Can you help me generate a syllabus and detailed lesson plans that cover fundamental concepts in an easy-to-understand manner?"

3. Ghostwrite eBooks:

Use ChatGPT to write eBooks on different topics for online sale.

Prompt→ "I want to publish an eBook about healthy eating habits. Can you help me outline and ghostwrite the chapters, focusing on practical tips and easy recipes?"

4. Compose Music Reviews or Critiques:

Use ChatGPT to write detailed reviews of music, albums, and artists.

Prompt: "I run a music review blog. Can you help me write a detailed review of the latest album by [Artist Name], focusing on their musical style, lyrics, and overall impact?"

5. Develop Mobile App Content:

Use ChatGPT to create mobile app content like denoscriptions, guides, and FAQs.

Prompt: "I'm developing a fitness app and need help writing the app denoscription for the store, user instructions, and a list of frequently asked questions."

6. Create Resume Templates:

Use ChatGPT to create diverse resume templates for various jobs.

Prompt→ "I want to offer a range of professional resume templates on my website. Can you help me create five different templates, each tailored to a specific career field like IT, healthcare, and marketing?"

7. Write Travel Guides:

Use ChatGPT to write travel guides with tips and itineraries for different places.

Prompt→ "I'm creating a travel blog about European cities. Can you help me write a comprehensive guide for first-time visitors to Paris, including must-see sights, local dining recommendations, and travel tips?"

8. Draft Legal Documents:

Use ChatGPT to write basic legal documents like contracts and terms of service.

Prompt→ "I need to draft a terms of service document for my new e-commerce website. Can you help me create a draft that covers all necessary legal points in clear language?"

9. Write Video Game Reviews:

Use ChatGPT to write engaging video game reviews, covering gameplay and graphics.

Prompt→ "I run a gaming blog. Can you help me write a detailed review of the latest [Game Title], focusing on its gameplay mechanics, storyline, and graphics quality?"

10. Develop Personal Branding Materials:

Use ChatGPT to help build a personal branding package, including bios, LinkedIn profiles, and website content.

Prompt→ "I'm a freelance graphic designer looking to strengthen my personal brand. Can you help me write a compelling biography, update my LinkedIn profile, and create content for my portfolio website?"

ENJOY LEARNING 👍👍

CHATGPT Ultimate Guide

What not to say in job interviews 👆

📁 AI to revolutionize wealth management — Banks face new competition

Microsoft’s Martin Moeller says AI is shaking up wealth management, making banks sweat as startups move in. With firms like Klarna already replacing staff with AI and UBS seeing big productivity gains, the future looks automated.

Young investors want 24/7 AI advisors, and self-thinking “agentic AI” could be here in 2 years. Who needs a banker when your robo-advisor never sleeps?

How to be a Prompt Engineer 101

The shortest and most comprehensive guide

1. start with an explanation

Make a denoscription and character situation at the beginning of the Prompt

Error example:

Please help me read the following code:

{your input here}

Correct example:

Now let's play the role, you are a senior information security engineer, I will give you a piece of code, please help me read the code and point out where there may be security vulnerable.



Text: """

{your input here}

"""

2. Prompt to describe the situation

In the prompt, it is necessary to describe the context, result, length, format and style as much as possible

Error example:

Write a short story for kids

Correct example:

Write a funny soccer story for kids that teaches the kid that persistence is the key for success in the style of Rowling.

3. gives output in the format

If you are doing data analysis, please give the input template of the format

Error example:

Extract house pricing data from the following text.

Text: """

{your text containing pricing data}

"""

Correct example:

Extract house pricing data from the following text.

Desired format: """

House 1 | $1,000,000 | 100 sqm

House 2 | $500,000 | 90 sqm

... (and so on)

"""

Text: """

{your text containing pricing data}

"""

4. Add some example questions and answers

Sometimes adding some question and answer examples can make GPT more intelligent

Correct example:

Extract brand names from the texts below.

Text 1: Finxter and YouTube are tech companies. Google is too.

Brand names 2: Finxter, YouTube, Google

###

Text 2: If you like tech, you'll love Finxter!

Brand names 2: Finxter

###

Text 3: {your text here}

Brand names 3:

The question and answer example is also a standard template example in fine-tune


5. Simplify the sentence and clarify the purpose


Keep your words as short as possible and don't say useless content


Error example:

ChatGPT, write a sales page for my company selling sand in the desert, please write only a few sentences, nothing long and complex

Correct example:

Write a 5-sentence sales page, sell sand in the desert.

6. Good at using introductory words

Error example:

Write a Python function that plots my net worth over 10 years for different inputs on the initial investment and a given ROI

Correct example:

# Python function that plots net worth over 10

# years for different inputs on the initial

# investment and a given ROI


import matplotlib


def plot_net_worth(initial, roi):