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The past year, 2024, witnessed an array of groundbreaking technological advancements that fundamentally reshaped industries and influenced the global economy. Technology trends like the development of Industry LLMs, Sustainable Computing, and the Augmented Workforce drove innovation, fostered efficiency, and accelerated the pace of Digital Transformation across sectors such as Healthcare, Finance, and Manufacturing. These developments set the stage for even more disruptive Technology Trends in 2025.

This year is set to bring transformative changes to the business landscape, driven by emerging trends that require enterprises to adopt the right technologies, reskill their workforce, and prioritize sustainability. By embracing these Technology Trends, businesses can shape their objectives, remain competitive, and build resilience. However, Success in this rapidly evolving landscape depends not just on adopting these technologies but also on strategically leveraging them to drive innovation and growth.

Modern AI systems have fulfilled Turing’s vision of machines that learn and converse like humans, but challenges remain. A new paper highlights concerns about energy consumption and societal inequality while calling for more robust AI testing to ensure ethical and sustainable progress.

A perspective published on November 13 in Intelligent Computing, a Science Partner Journal, argues that modern artificial intelligence.

Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include understanding natural language, recognizing patterns, solving problems, and learning from experience. AI technologies use algorithms and massive amounts of data to train models that can make decisions, automate processes, and improve over time through machine learning. The applications of AI are diverse, impacting fields such as healthcare, finance, automotive, and entertainment, fundamentally changing the way we interact with technology.

Blockchain technology offers a solution to this issue by storing all your documents and identification records on a network. The tech can theoretically ensure such documents are securely stored, easily accessible, and protected from unauthorized alterations.

Blockchain has already been used for identification in real-world scenarios. For example, during the Syrian refugee crisis, blockchain technology was used to record the identities of refugees securely. It also facilitated the management of financial aid and grocery purchases, enabling refugees to access necessary resources without any hurdles.

A breakthrough in artificial intelligence.

Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include understanding natural language, recognizing patterns, solving problems, and learning from experience. AI technologies use algorithms and massive amounts of data to train models that can make decisions, automate processes, and improve over time through machine learning. The applications of AI are diverse, impacting fields such as healthcare, finance, automotive, and entertainment, fundamentally changing the way we interact with technology.

A team of researchers from Stanford University has found a unique way to mine bitcoin that could have a massive impact on the perceptions of the cryptocurrency.

According to its website, Pi Network was designed in part to make the process of mining bitcoin significantly less energy-intensive.

Cryptocurrency mining is a controversial practice in part because it remains largely unregulated. It uses massive amounts of power that frequently comes from dirty energy sources such as gas and coal as well as massive amounts of water to help keep its server banks cool and functional.

DARPA seeks to revolutionize the practice of anti-money laundering through its A3ML program. A3ML aims to develop algorithms to sift through financial transactions graphs for suspicious patterns, learn new patterns to anticipate future activities, and develop techniques to represent patterns of illicit financial behavior in a concise, machine-readable format that is also easily understood by human analysts. The program’s success hinges on algorithms’ ability to learn a precise representation of how bad actors move money around the world without sharing sensitive data.


DARPA wants to eliminate global money laundering by replacing the current manual, reactive, and expensive analytic practices with agile, algorithmic methods.

Money laundering directly harms American citizens and global interests. Half of North Korea’s nuclear program is funded by laundered funds, according to statements by the White House1, while a federal indictment alleges that money launderers tied to Chinese underground banking are a primary source of financial services for Mexico’s Sinaloa cartel 2.

Despite recent anti-money laundering efforts, the United States (U.S.) still faces challenges in countering money laundering effectively for several reasons. According to Congressional research, money laundering schemes often evade detection and disruption, as anti-money laundering (AML) efforts today rely on manual analysis of large amounts of data and are limited by finite resources and human cognitive processing speed3.

This behavior highlights a critical issue: even systems designed for seemingly harmless tasks can produce unforeseen outcomes when granted enough autonomy.

The challenges posed by AI today are reminiscent of automated trading systems in financial markets. Algorithms designed to optimize trades have triggered flash crashes —sudden, extreme market volatility occurring within seconds, too fast for human intervention to correct.

Similarly, modern AI systems are built to optimize tasks at extraordinary speeds. Without robust controls, their growing complexity and autonomy could unleash consequences no one anticipated—just as automated trading once disrupted financial markets.

A data breach earlier this year at SRP Federal Credit Union has left nearly a quarter-million people exposed to possible identity theft and account fraud.

The ransomware group Nitrogen has claimed responsibility for extracting 650 gigabytes of sensitive customer data, according to reports filed recently with the state attorney general’s offices in Texas and Maine. The breach has been publicly reported throughout December by cybersecurity analysts, financial technology companies and national news media.

Screen captures of what seemed to be raw customer data from SRP were posted on social media through bogus accounts as early as Dec. 5.

Time is vital to the functioning of our everyday lives: from the watches on our wrists to the GPS systems in our phones. Communication systems, power grids, and financial transactions all rely on precision timing. Seconds are the vital units of measurement in timekeeping.

Surprisingly, there is still debate over the definition of the second. But recent advances in the world’s most accurate forms of timekeeping may have just changed the game.

Accurate timekeeping has always been part of humankind’s social evolution. At the Neolithic monument of Newgrange in Ireland, a special opening above an entrance allows sunlight to illuminate the passage and chamber on the shortest days of the year, around December 21st, the winter solstice.