The most talked-about tech entrepreneur of the time: Elon Musk

 

Elon Musk. Possibly the most talked-about tech entrepreneur of the time. Love him or hate him, the guy's fingerprints are all over the future. Let's break him down a bit:

⚡ Quick Snapshot of Elon Musk

• Born: 1971, South Africa
• Founder/CEO/Big Brain Behind:
• Tesla (Electric cars, energy)
• SpaceX (Rockets, Starlink, Mars dreams)
• Neuralink (Brain-machine interfaces)
• The Boring Company (Underground transport)
• X (formerly Twitter) (Social media)
• xAI (His AI company—rivaling OpenAI, Google, etc.)
• Was also a co-founder of PayPal

🚀 Why He Matters for the Future

1. Space Travel & Colonization

• SpaceX made rockets reusable. Huge cost savings.
• Plans to colonize Mars by the 2030s. (He says, “We must become a multi-planetary species.”)
• Starship (his big rocket) is being tested to carry cargo—and eventually, people—beyond Earth.

2. Revolutionizing Transportation

• Tesla led the EV revolution. Now every major car company is chasing them.
• Autonomous driving is still a work in progress, but he's pushing hard for AI-driven vehicles.
• Hyperloop and Boring Company aim to redefine how we move underground and between cities.

3. AI, Brains & Ethics

• He’s both excited and terrified of AI.
• Neuralink aims to merge humans with AI—brain implants that could help with memory loss, paralysis, and eventually human-AI symbiosis.
• Now running xAI, his own AI lab to create “truth-seeking AI.”

4. Social Media + Influence

• Took over Twitter/X in 2022 to promote “free speech”—led to a lot of chaos and reinvention.
• He's outspoken, polarizing, and basically posts memes one second, deep philosophy the next.

🤖 Criticisms & Controversy

• Accused of overpromising timelines (Mars by 2024? Not quite).
• Some worry about too much power in one person’s hands (space, internet, cars, brains, AI, media? That’s a lot).
• Has faced backlash for his social media behavior, company culture issues, and regulatory clashes.

🧠 Why People Pay Attention to Him

• He does things most people only talk about.
• He’s not afraid to take massive risks (almost went bankrupt multiple times).
• Even if he fails, he shifts the conversation around what’s possible.

🌌 Musk's Vision of the Future

• Humans on Mars
• AI as a helpful partner (not overlord)
• Global internet access
• Cleaner energy everywhere
• Mind-machine interfaces
• Faster-than-plane underground travel

 

The Future of Data Science: Careers and How to Get Started

 

Data Science in a Changing Landscape:

As industries increasingly rely on data-driven decision-making, the field of data science is evolving to meet new challenges and opportunities. Emerging technologies are transforming how data is collected, analyzed, and utilized, reshaping the skills and knowledge required for future professionals. Understanding these trends is crucial for those entering the field, as it will help guide their education and career paths.

In the coming years, significant advancements in artificial intelligence (AI), machine learning (ML), and quantum computing will redefine data processing and analytics. As these technologies evolve, data scientists must stay ahead of the curve. This article explores the key trends shaping data science, what aspiring professionals should anticipate, and how to embark on a successful career in the field.

Understanding Data Science:

Before exploring the future of data science, it's essential to understand its fundamental elements.

The Evolution of Data Science:

Data science has its roots in statistics and computer science, initially focusing on basic data processing and analysis. The 1960s and 1970s saw the rise of data warehousing and business intelligence. By the early 2000s, machine learning and AI became integral to data science, leading to sophisticated, data-driven decision-making. The explosion of big data in the past decade has further accelerated this evolution, making data science a crucial driver of innovation across industries such as finance, healthcare, and technology.

Core Technologies Driving Data Science:

Key components of data science include:

• Data Warehousing & Mining – The foundation of data storage and retrieval.

• Cloud Computing – Provides scalable, flexible data storage and processing solutions.

• Machine Learning & AI – Enables predictive analytics, automation, and intelligent decision-making.

• Data Visualization – Tools like Tableau and Power BI help translate complex data into actionable insights.

Preparing for a Career in Data Science: 

Aspiring data scientists should equip themselves with the right skills and resources to thrive in this rapidly evolving field.

Essential Skills for Beginners: 

To succeed in data science, developing a strong foundation in mathematics, statistics, and programming is essential. Key skills include:

• Programming Languages: Python, R, and SQL for data analysis and manipulation.

• Understanding of Algorithms & Data Structures: Critical for building machine learning models.

• Data Visualization & Cloud Computing: Provides a competitive edge in real-world applications.

Getting Started with Data Science Tools:

Popular tools like Jupyter Notebooks, TensorFlow, and Tableau are essential for data analysis and machine learning. Online platforms such as DataCamp and edX offer beginner-friendly courses, providing hands-on experience with key tools and techniques.

A Step-by-Step Guide to Becoming a Data Scientist:

Step 1: Master Data Analysis & Management:

Understanding data collection, cleaning, and organization is crucial. Learn SQL, Excel, and data warehousing concepts to develop strong foundational skills.

Step 2: Dive into Machine Learning & AI:

Build predictive models using algorithms like linear regression, decision trees, and neural networks. AI-powered automation is an essential skill in modern data science.

Step 3: Implement Big Data Solutions:

Gain experience with big data frameworks like Hadoop and Spark to handle large datasets efficiently. Understanding these technologies prepares you for data-intensive environments.

Step 4: Explore Advanced Analytics & Visualization:

Master advanced analytics techniques such as time-series analysis and geospatial visualization using tools like Tableau, Power BI, and D3.js.

Emerging Technologies Shaping Data Science:

The Impact of Quantum Computing:

Quantum computing has the potential to revolutionize data science by offering unprecedented computational power. Unlike traditional computers, quantum computers use qubits, enabling complex calculations at unimaginable speeds. This advancement could significantly enhance optimization problems in cryptography, financial modeling, and drug discovery.

Breakthroughs in Predictive Analytics:

The integration of deep learning techniques allows predictive analytics to process vast amounts of unstructured data, improving customer behavior forecasting, fraud detection, and risk management. Real-time data processing is also enhancing decision-making capabilities across industries.

Trends to Watch in Data Science:

Growing Importance of Data Ethics & Privacy:

With increased data collection, concerns over ethics and privacy are rising. Stricter regulations, such as GDPR and CCPA, require data scientists to ensure compliance and ethical data usage.

Changing Job Market Demands:

The job market is shifting towards candidates who possess technical expertise along with business acumen. The U.S. Bureau of Labor Statistics projects a 36% growth in data science roles between 2023 and 2033, making it one of the fastest-growing career fields.

Real-World Applications of Advanced Data Science:

Healthcare & Biotechnology Innovations:

Data science is revolutionizing healthcare through personalized medicine and AI-driven drug discovery. Companies like GNS Healthcare use machine learning to tailor treatments, while AstraZeneca leverages AI for faster drug development.

Financial Services Advancements:

Financial institutions utilize data science for fraud detection, risk assessment, and personalized services. JPMorgan Chase employs AI-driven algorithms to identify fraudulent transactions, while PayPal uses predictive analytics to enhance customer experiences.

Challenges in Data Science:

Addressing Data Security Concerns:

High-profile data breaches, such as the Facebook-Cambridge Analytica scandal, highlight the need for stringent data governance. Organizations are adopting encryption and regulatory compliance measures to enhance data security.

Bridging the Skills Gap in Emerging Technologies:

The rapid evolution of AI and quantum computing has created a skills gap in the workforce. Companies like IBM and Google are offering specialized training to address this challenge and equip professionals with advanced expertise.

Job Demand for Data Scientists:

The demand for data scientists remains strong worldwide in 2025. According to the World Economic Forum, data science and AI-related roles are among the fastest-growing careers globally. Businesses in various industries—such as finance, healthcare, technology, and e-commerce—are actively hiring data professionals to manage and analyze large datasets. Additionally, AI-driven analytics, cloud computing, and big data are further driving demand for skilled data scientists​.

Data Scientist Salaries by Country:

Data scientist salaries vary based on factors such as location, experience, specialization, and industry. Below are the estimated salaries for 2025:

• United States: $100,000 - $150,000 per year, with top professionals earning over $200,000, especially in tech hubs like San Francisco, New York, and Seattle​.

• United Kingdom: £60,000 - £90,000, with senior-level roles reaching over £100,000, particularly in London​.

• India: ₹6,00,000 - ₹20,00,000 for mid-level professionals, while senior data scientists (8+ years) can earn ₹30,00,000+ per year​.

• Germany: €50,000 - €90,000, with higher salaries in Berlin, Munich, and Frankfurt​.

• Dubai (UAE): AED 120,000 - AED 350,000 per year, depending on experience and industry​.

• Morocco: MAD 120,000 - MAD 250,000 per year, with the highest demand in telecom, finance, and government sectors​.

Factors Affecting Data Scientist Salaries:

• Specialization: Expertise in AI, machine learning (ML), deep learning, and cloud technologies (AWS, Azure, Google Cloud) significantly increase salaries.

• Industry: The finance, healthcare, and technology sectors offer the most lucrative salaries.

• Certifications & Skills: Certifications like Google’s Professional Data Engineer and Microsoft’s Azure Data Scientist boost employability​.

• Experience Level: Senior professionals (8+ years) often earn twice as much as entry-level data scientists.

Is Data Science Still a Good Career in 2025?

Yes! The field continues to grow, offering remote work opportunities, high salaries, and job security. However, continuous learning in AI, cloud computing, and big data analytics is essential to staying relevant.

Latest Developments in Artificial Intelligence of Bangladesh

 

1. AI Integration in Various Sectors

Bangladesh is making progress in AI adoption across industries such as telecom, finance, and retail. Companies like Intelligent Machines (IM) have successfully implemented AI solutions, improving business efficiency. For example, Unilever used AI-powered Fordo for precision marketing, achieving a 260% increase in performance, while bKash saw a 15% rise in monthly onboarding due to AI-powered automation. Additionally, Telenor reduced its KYC costs by 92.5% using AI-driven document verification tools​

2. Bangladesh’s AI Policy and Regulations

The Bangladesh government has drafted a National AI Policy that aims to guide AI development in 10 key sectors, including finance, education, and climate change. The policy emphasizes ethical AI use, data governance, and skill development, along with the establishment of a National AI Center of Excellence​

To regulate AI usage, the government is also working on the AI Act 2024, which is expected to be finalized by September 2025. The law aims to address AI risks while promoting innovation and aligning with the country's Smart Bangladesh Vision 2041​

3. Challenges in AI Adoption

Despite progress, Bangladesh faces challenges such as a lack of digital infrastructure, AI skill shortages, and limited data governance frameworks. The country's AI Preparedness Index score (0.38) is lower than that of regional competitors, indicating the need for faster workforce development and regulatory improvements​

4. Future Prospects

Experts believe that investing in AI education, research, and policy implementation can position Bangladesh as an AI-driven economy. Successful execution of AI strategies could enhance productivity, attract investments, and drive innovation​

The world is entering the era of wireless electricity !

 

Since the first electricity generation at the Pearl Power Station in New York in 1882, the only method of electricity supply has been through wired connections. However, in the current era, this method is not always effective. In many remote areas or in space, it is impossible to use wires for electricity supply. Additionally, due to climate change, the demand for electricity and its supply accessibility have become even more important. Therefore, scientists have been working for a long time on a new method of electricity supply without wires. This technology is called ‘Power Beaming.’ For over a century, scientists have been trying to transmit electricity through microwaves, radio waves, and lasers. The idea was first proposed by scientist Nikola Tesla, who suggested using the Earth's ionosphere to create a method of wireless electricity transmission. Although his research did not come to fruition, the pursuit of wireless electricity continued. After World War II, this technology began to develop further. In 1964, American engineer William C. Brown was able to power a small helicopter for 10 hours by transmitting electricity via microwaves. Later, in 1975, NASA scientist Richard Dickson successfully transmitted 30 kilowatts of electricity over a distance of one mile, though its efficiency was still not sufficient at the time.

However, due to advancements in technology, it is now on the path to becoming a reality. The progress in computers, photovoltaic technology, lasers, and transistors has made power beaming more effective. This technology is particularly gaining importance in reducing the use of fossil fuels. Currently, a New Zealand-based company, EMROD, is implementing a system that transmits electricity via microwaves directly from the power grid. Meanwhile, U.S.-based Reach Power is working on a method to supply electricity over a 25-kilometer range using radio waves. This technology is becoming increasingly important in the military sector and for commercial use. The United States, Europe, and Japan are investing heavily in this technology. Specifically, Japan’s space agency, JAXA, plans to implement wireless electricity supply from space by 2030. At present, this technology is being used for low-power applications, such as smart sensors, motion detectors, and smart displays in supermarkets. Gradually, it will be used on a larger scale. Scientists predict that this will soon become a reality, and in the future, wireless electricity will become an integral part of our daily lives.

Three professions that will remain resilient against AI automation​: Bill Gates

 

Bill Gates has identified three professions that he believes will remain resilient against AI automation: coders, biologists, and energy experts. While artificial intelligence is rapidly transforming industries and automating many jobs, Gates argues that these fields require human creativity, intuition, and decision-making that AI cannot fully replicate.

1. Coders – Despite AI’s growing ability to generate code, human programmers are still essential for debugging, refining algorithms, and improving AI models. Gates emphasizes that AI cannot self-improve without human oversight, making software developers integral to the technology's evolution​.

2. Biologists – AI can assist in analyzing medical data, diagnosing diseases, and scanning DNA, but it lacks the creativity and hypothesis-driven thinking required for scientific breakthroughs. Biologists will continue to lead innovation in medicine and life sciences, with AI serving as a supporting tool rather than a replacement​.

3. Energy Experts – The complexity of the energy sector, including grid management, regulatory challenges, and sustainable energy solutions, makes full automation impractical. Human oversight is critical for decision-making, crisis management, and long-term planning in the industry​.

Gates also pointed out that while AI will reshape the job market, the best way to stay competitive is to integrate AI into one’s work rather than resist it. He even predicted a shift toward shorter workweeks as automation takes over repetitive tasks, requiring professionals to focus on higher-level problem-solving.

A Last Breath: A Poignant Sculpture of Humanity's Future

 

In a haunting and thought-provoking sculpture, an artist has captured a chilling vision of the future, portraying a human figure struggling to take the final breath of oxygen from the last tree on Earth. Titled "A Last Breath," the piece serves as a powerful reminder of the catastrophic consequences of environmental neglect and the urgent need to protect our planet's natural resources.

The sculpture features a gaunt, weary human figure, their face pressed against the trunk of a dying tree. Its branches are stripped bare, its leaves long vanished, and its bark cracked and parched. The figure's lungs seem to labor in vain, struggling to extract the last vestiges of life-sustaining oxygen from the tree, symbolizing a futile fight for survival in a world devoid of vitality.

The artist's use of contrasting materials heightens the emotional weight of the work. The human form is rendered in a delicate, almost ethereal material, while the tree's trunk is a deep, earthy brown. The surrounding landscape is bleak and barren, with dust and debris scattered around the tree's base, reinforcing the desolation of the scene.

"A Last Breath" is a striking and unsettling piece that forces viewers to confront the very real possibility of a future where humanity has exhausted the Earth's resources. This sculpture is a sobering call to action, urging us to recognize the critical importance of sustainability, conservation, and the responsible care of our planet’s natural wealth.

Driving the Future of Transportation: SES AI's NVIDIA-Powered Breakthrough in Electric Vehicles

 

Accelerating EV Innovation: How SES AI and NVIDIA are Transforming Battery Technology

Electric vehicles (EVs) are reshaping transportation, but widespread adoption still faces challenges such as cost, battery longevity, and driving range. At the core of these issues lies battery technology—specifically, the electrolyte, a crucial component that determines charging speed, power output, stability, and safety.

To overcome these barriers, researchers are leveraging AI-driven approaches to accelerate the discovery of advanced battery materials.

Revolutionizing Battery Innovation with AI

SES AI, a leader in next-generation battery technology, is harnessing the power of NVIDIA’s cutting-edge hardware and software ecosystem to drive breakthroughs in materials discovery. By integrating domain-adapted large language models (LLMs) with AI-driven simulations on GPUs, SES AI condenses decades of research into mere months—unlocking transformative advancements in EV battery performance.

SES AI’s AI-Powered Battery Development Approach

SES AI’s pioneering research follows a structured, AI-enhanced methodology:

Mapping the Molecular Universe

SES AI is constructing an extensive molecular database to catalog the physical and chemical properties of millions of small molecules. Central to this effort is AIMNet2 (Atoms in Molecules Neural Network)—a neural network potential developed by Carnegie Mellon University’s Isayev Lab. AIMNet2 significantly enhances the speed and accuracy of molecular simulations, expediting property predictions.

"Our goal is to map the properties of small molecules to develop superior energy storage solutions—for applications ranging from flying cars to humanoid robots and data centers," says Qichao Hu, CEO of SES AI. "With our collaboration with NVIDIA and the use of AIMNet2, we've accelerated this process from thousands of years to just a few months."

Advancing Chemistry LLMs

By integrating domain-specific Chemistry LLMs, SES AI enhances reasoning capabilities, streamlining the discovery of novel battery materials and providing researchers with powerful tools for next-generation battery development.

Constructing High-Performance Batteries

SES AI rapidly tests and refines candidate materials in prototypes, demonstrating significant performance improvements and paving the way for safer, longer-lasting EV batteries.

Leveraging NVIDIA’s AI Platform for Breakthroughs

SES AI relies on NVIDIA’s powerful AI platform to explore a vast solution space of over 100 million molecules. Their workflow integrates accelerated molecular simulations, optimized data exploration, and enhanced LLM-driven insights, pushing the boundaries of battery innovation.

By combining AI, advanced simulations, and high-performance computing, SES AI and NVIDIA are accelerating the future of EVs—bringing us closer to more efficient, affordable, and sustainable electric transportation.

                                          Figure 1. SES AI’s NVIDIA-enabled workflow

Enhancing Molecular Simulations with NVIDIA ALCHEMI

SES AI leverages NVIDIA ALCHEMI to accelerate molecular simulations, utilizing Batched Geometric Relaxation (BGR) with AIMNet2 NIM microservice and the Batched Density Functional Theory (DFT) microservice. These cutting-edge tools enable rapid molecular structure simulations and the calculation of essential properties, such as the HOMO-LUMO gap, which defines a molecule’s electronic characteristics and energy storage potential.

The BGR AIMNet2 NIM microservice streamlines the search for the most stable molecular configuration, significantly reducing computational time. Meanwhile, the Batched DFT microservice enhances GPU4PySCF—an open-source, GPU-accelerated Python package integrated into the Python-based Simulations of Chemistry Framework (PySCF)—boosting the efficiency of quantum chemistry calculations.

By integrating these innovations, SES AI achieves unprecedented speed and accuracy in molecular simulations, accelerating breakthroughs in battery materials and energy storage technology.

Accelerating Battery Innovation with NVIDIA-Powered AI

Demo: Boosting Simulations with NVIDIA ALCHEMI BGR AIMNet2 NIM

Interactive Data Exploration

SES AI leverages NVIDIA cuML to accelerate UMAP for dimensionality reduction and HDBSCAN for clustering, enabling the creation of interactive molecular maps. These AI-driven tools help researchers analyze millions of molecules efficiently, uncover hidden patterns, and rapidly identify promising candidates for next-generation battery materials.

Training Chemistry LLMs

To train its Chemistry LLM on 35 billion tokens sourced from 17 million scientific papers, SES AI utilized NVIDIA DGX Cloud and NVIDIA NeMo, a framework for building domain-specific generative models.

For enhanced accuracy, SES AI applied NeMo Curator features, including:

• Exact deduplication

• Number and word count filters

• Repeated line and non-alphanumeric filters

These optimizations resulted in a customized Chemistry LLM that surpasses its base model in molecular ranking and scientific reasoning—delivering faster, more precise insights for battery material discovery.

Breakthrough Results: Transforming Battery Technology

The collaboration between SES AI and NVIDIA has led to groundbreaking advancements:

• 17 candidate materials identified – Two already synthesized and tested at SES AI’s Electrolyte Foundry in Woburn, Massachusetts.

• 20% increase in battery cycle life – Early tests reveal significant improvements in battery longevity.

• 1,600x simulation acceleration & 2x energy efficiency – Achieved through NVIDIA H100 GPUs, ALCHEMI’s BGR AIMNet2 NIM, and Batched DFT Microservice.

• 10x faster data exploration – Enabled by NVIDIA cuML.

• 25% improvement in LLM accuracy – Chemistry LLM, trained on NVIDIA DGX Cloud and NeMo, outperforms the base model in molecular ranking and reasoning.

Innovations Driving the Future of Batteries

These advancements have fueled the development of next-generation battery technologies:

• Lithium-metal batteries – Offering superior performance and safety.

• High-silicon lithium-ion batteries – A newly identified solvent molecule addresses expansion challenges without emitting harmful gases at high temperatures.

Driving Sustainability Through Accelerated Innovation

Traditionally, discovering a breakthrough battery electrolyte required five years. Today, with SES AI and NVIDIA’s cutting-edge technologies, transformative advancements are emerging every six months. These innovations are shaping the future of EV batteries—enhancing performance, safety, and longevity while significantly reducing greenhouse gas emissions and promoting sustainable practices worldwide.

By accelerating materials discovery, SES AI and NVIDIA are not only propelling technological progress but also stimulating economic growth and reinforcing global efforts to combat climate change.