Rather than discussing AI related topics, this week I wanted to try something out, building a simple AI tool that can generate captions for images. I was able to complete this in under 45-minutes, and I’m going to walk you through the process, step-by-step.
Step 1: Setting up the Folder in Terminal
First things first, I opened Terminal on my Mac (you can find it in Applications > Utilities). Then, I ran these commands to create a folder and go inside it:
mkdir ai-image-captioning
cd ai-image-captioning
This creates an empty folder to store everything for the AI model.
Step 2: Setting up VS Code
I opened up VS Code directly from the Terminal by typing:
code .
This opens up VS Code in the current folder, ai-image-captioning. If you don’t have VS Code already downloaded, you can do that on the website.
Step 3: Downloading AI Model and Script
I wasn’t sure where the script was, so I had to find a way to call the caption generator script for the AI. So, I found a GitHub repository that had the necessary script and cloned it to my folder by doing:
Once that was completed, the script for caption_generator.py was ready
Step 4: Installing the Python Libraries That Are Needed
The caption_generator.py script needs a few Python libraries to work, so I installed them using this code (your code will not run unless you download these!):
Once I hit Enter, the AI processed the image and generated this caption:
“Generated Caption: a dog sitting in the grass”
Now you’re done! You have successfully completed making an AI caption generator.
But, how does this work?
Make sure to read my next post to find out all about this. 🙂
Resource:
Wang, Jim. “What Is Image Captioning and How to Use Python to Generate Caption from an Image?” Medium, Medium, 14 Sept. 2024, medium.com/@jimwang3589/what-is-image-captioning-and-how-to-use-python-to-generate-caption-from-an-image-98a9eb6be06d.
When people think about AI, they usually think of ChatGPT, self-driving cars, or robots. However, behind all of this intelligence is something that may seem boring at first, matrices. Even though they just look like grids of numbers, they are actually one of the most important tools in AI. They help machines process information, recognize patterns, and make decisions.
Simply put, a matrix is a set of numbers arranged in rows and columns. Here’s an example of a simple 4×4:
How AI Uses Matrices:
Storing and Processing Data: to deal with large amount of data, AI models use matrices to help organize it
Ex: Images are made up of tiny pixels, and each pixel has a brightness value. These values can be stored in a matrix, allowing AI to analyze the image and see patterns
Editing and Transforming Images:AI uses a type of matrices, transformation matrices, to move, rotate, or stretch images while keeping everything else aligned
Ex: In Instagram or Snapchat filters, transformation matrices are used to make sure the filter stays in place even when you move your head.
Neural Networks and Matrix Multiplication: Neural networks are essentially the “brains” of AI, and they reply on matrix multiplication to process information.
Ex: Every connection between neurons (small units in AI models), are stored in a matrix. When AI learns, it’s basically just adjusting the values to improve accuracy.
Understanding Language: AI chatbots do not just memorize words, instead they use matrices to predict what word should come next. Every word in a sentence can be converted into a vector, a type of matrix, and AI compares these to form possible responses
Ex: When you are using ChatGPT and it gives you possible questions to ask as you are typing, it is using vector matrices to predict what you are asking.
Why do Matrices Matter?
They are the foundation of AI! Every single time you use Google Translate, scroll through your FYP on TikTok, use a Snap or Instagram filter, or talk to a chatbot, you’re using AI powered matrices!
Artificial sweeteners are found in a lot of the foods and drinks we consume, and they’re often advertised as being better alternatives to sugar. However, there’s been a lot of debate about whether they’re actually safe. Some people think they might be linked to serious health problems, like cancer. In her literature review, Ayana Rao explores whether artificial sweeteners are really a cause of cancer. She goes over the research, what studies say about the risks, and why this issue is still being talked about today.
The Bitter Truth Behind Artificial Sweeteners and Cancer Risk
Ayana Rao
Abstract
As obesity rates continue to rise around the world, many turn to low-sugar or sugar-free alternatives to avoid health complications. Diet and sugar-free foods and beverages utilize artificial sweeteners to achieve similar tastes while lacking the calories that table sugar has. However, concerns have been raised regarding the potential role artificial sweeteners may play in causing cancer, with numerous artificial sweeteners having preliminary data that suggests associations with cancers. In this review, we present the latest evidence for cancer-associated risk amongst US-approved artificial sweeteners and identify gaps for future research.
Introduction
The global rise in obesity has prompted the widespread adoption of low-calorie, non-nutritive sweeteners, also known as artificial sweeteners, in the food and beverage industry. These substitutes offer the appeal of sweetness without the added calories of sugar, making them attractive for weight management and mitigating health risks associated with excessive sugar intake. Approved artificial sweeteners vary by country; in the United States (US), the Federal Drug Administration (FDA)-approved artificial sweeteners include acesulfame-potassium, aspartame, neotame, saccharin, sucralose, and advantame ( High-Intensity Sweeteners , n.d.). When artificial sweeteners were first FDA-approved, little attention was given to the potential long-term consequences of their consumption, including the risk of malignancy. Despite regulatory approval, concerns regarding the possible carcinogenicity of artificial sweeteners have persisted since the 1960s, when cyclamate was banned due to preliminary evidence of bladder cancer in rats. Although subsequent studies have not consistently replicated these findings, the incident underscores the importance of rigorous investigation into the long-term health effects of these widely consumed additives.
Over 95% of adults consume artificial sweeteners within their lifetime (Popkin & Nielsen, 2003). Many turn to artificial sweeteners as a measure against obesity and related diseases such as type 2 diabetes (Daher et al., 2022). The widespread adoption of artificial sweeteners has prompted researchers to examine the underlying health effects caused by consuming these low-calorie substitutes. To date, several artificial sweeteners have been linked to different cancers, however, the data remains contradictory and inconclusive (Arnold, 1983; Chi et al., 2018; Debras et al., 2022, 2022; Mann et al., 2000; Mukhopadhyay et al., 2000; Otabe et al., 2011; Schernhammer et al., 2012; Soffritti et al., 2006). This review aims to critically examine the evidence linking FDA-approved artificial sweeteners to cancer risk, highlighting areas for further research.
Methods
A systematic literature search was conducted using PubMed and Google Scholar, focusing on studies published between February 2018 and April 2024. The search terms included “non-nutritive sweeteners,” “artificial sweeteners,” “neoplasms,” and specific names of the six FDA-approved sweeteners. Studies in any language and with any study design were considered. Additional studies were identified through reference mining and expert recommendations.
Discussion
Aspartame
Aspartame was first approved by the FDA in 1974 (Nutrition, 2023). As a whole, aspartame remains one of the most studied artificial sweeteners to date (Nutrition, 2024). Studies linking artificial sweeteners and cancer predominantly evaluate aspartame, with data in both animal and human studies providing a range of connections to different carcinogens. Two studies suggest a link between aspartame consumption and the development of blood cancers such as leukemia and lymphoma (Schernhammer et al., 2012; Soffritti et al., 2006). In these studies, researchers treated mice with aspartame in their water, with a water-only group serving as a control (Dooley et al., 2017; EFSA Panel on Food Additives and Nutrient Sources Added to Food (ANS), 2013; Hagiwara et al., 1984). Across nearly 500 mice from these studies, researchers found similar findings, namely that the mice consuming aspartame had a higher risk of developing leukemia and lymphoma than the control mice. A similar experiment was conducted in rats, showing a sex-specific association between aspartame consumption and lymphoma development in male rats (Schernhammer et al., 2012).
Interestingly, a similar sex-specific finding occurred in a longitudinal human study assessing aspartame and the rate of lymphoma development. For this 22-year-long study, participants (N = 125,028) were asked to fill out a questionnaire about their aspartame use (focusing on diet sodas, the most popular mode of ingesting aspartame) and then personal medical history of malignancy. The study found a significant positive association between drinking one or more aspartame-sweetened sodas per day and a 30% increased risk of developing non-Hodgkin lymphoma in the male cohort. However, no significant association was found in the female cohort nor when all genders were combined and analyzed together. There was no clear reason for the difference in outcomes based on sex, though the results still do raise concerns about possible carcinogenic properties of aspartame (Schernhammer et al., 2012). Together, this preliminary evidence for increased carcinogenicity of aspartame in male mice and humans supports further research into the differential impact of aspartame based on biological sex.
Links between aspartame consumption and several other malignancies have been found in individual, small studies involving mice. This includes breast, liver, (Chi et al., 2018) lung, bladder, brain, and nerve cancer (Soffritti et al., 2006 ; Dooley et al., 2017; EFSA Panel on Food Additives and Nutrient Sources Added to Food (ANS), 2013). On the other hand, some small studies conducted on mice have found no link between aspartame and pancreatic, bladder brain, and liver cancers (Alkafafy et al., 2015; Ringel et al., 2022 ). The mixed findings of these small, animal-based studies warrant further investigation, especially in human subjects.
The impact of aspartame on carcinogenesis remains highly debated, most recently with the International Agency for Research on Cancer concluding that it is “possibly carcinogenic” (Nutrition, 2024). More data is needed to fully characterize aspartame’s impact on the risk of cancer development. Future areas of study should focus on expanding research to involve more humans now that aspartame has been on the market and widely consumed for over four decades (Czarnecka et al., 2021). Overall, the evidence for aspartame’s association with leukemia and lymphoma is the strongest and most well-studied. Several other studies have found mixed results with various other solid tumor types. While associations with cancer have been demonstrated, replication of these findings and additional research are required to establish conclusive claims.
Saccharin
Saccharin is a non-caloric sweetener used in many diet sodas and foods. Talks on cancer risk have been controversial for centuries. Existing studies on the carcinogenicity of saccharin are mainly focused on mice. While saccharin has been proven to induce higher rates of DNA damage compared to aspartame, (Bandyopadhyay et al., 2008) some studies failed to find a link between saccharin bearing any carcinogenic risk (Debras et al., 2022; NHANES – About the National Health and Nutrition Examination Survey , 2023; NHANES III REFERENCE MANUALS AND REPORTS , n.d.).
In 2023, a meta-analysis evaluating associations between endometrial cancer and consumption of artificial sweeteners, including saccharin, found no difference in the incidence rate of endometrial cancer between individuals exposed to artificial sweeteners and those who were not (Ringel et al., 2022). To our knowledge, no other studies on the association between endometrial cancer and saccharin exist at the time of this review (Li et al., 2024). Three studies, taking place over two generations of mice, investigated the association between saccharin and bladder cancer and found that all showed that 5-7.5% sodium saccharin in diet from birth to death leads to increased bladder cancer rates, specifically in male mice (Armstrong & Doll, 1975; Hicks & Chowaniec, 1977; Kessler, 1976; Morgan & Jain, 1974). These findings were supported by a toxicological and epidemiological study on mice, where they administered different doses of saccharin in mice into the mice’s diet, and found a correlation between saccharin consumption and bladder cancer (Suez et al., 2015). Presently, there have been no human-based studies evaluating saccharin and bladder cancer.
Saccharin’s increasing presence in daily diets contributes towards weight loss and helping diabetes makes it crucial that future areas of research should focus more on saccharin’s effect on the carcinogenicity of other cancers linked to similar artificial sweeteners, such as its close relative aspartame’s relation with leukemia, non-Hodgkin’s lymphoma, and other related health issues.
Neotame
Neotame has been tested on several animal species, such as Sprague-Dawley rats, mice, beagle dogs, and New Zealand Rabbits (Chi et al., 2018). In a study with mice (N=10), clean water was administered to the control groups, and water containing neotame was administered to the treatment group for 4 weeks. Researchers found that mice consuming neotame had no difference in gut taxonomy or fecal metabolomes. Numerous sources have found neotame to be non-carcinogenic, (Nofre, 2000; Satyavathi et al., 2010) and safe in other health aspects as a diet additive (Chi et al., 2018). While neotame is a rarely used artificial sweetener compared to its competitors, future studies that reinforce its safety may lead the way for its broader use.
Acesulfame-Potassium
Acesulfame-Potassium (acesulfame-K) is a non-caloric sweetener around 120 times sweeter than sucrose and is highly water-soluble. Its structure is similar and comparable to aspartame. acesulfame-K is often blended with other sweeteners, such as sucralose or aspartame, to mask the bitter taste (Chattopadhyay et al., 2014). It is often used in a range of baked goods, gum, spreads, mouthwashes, and dairy products ( What Is Acesulfame Potassium, and Is It Good or Bad for You? , 2020). Only one study in human adults (n=102,865) characterized the association of acesulfame-K and cancer and found it to increase cancer risk in a similar profile to that of aspartame, including various types of breast, prostate, and obesity-related cancers (Debras et al., 2022).
Another study conducted on albino Swiss mice aged 8-10 weeks found that a mixture of aspartame and acesulfame-potassium wasn’t found to increase carcinogenicity or chromosomal abnormalities in the test group (Mukhopadhyay et al., 2000). Given the prevalent use of acesulfame-potassium in weight loss and diet culture. Future areas of research should aim to use acesulfame-k in experiments to search for cancers that other related sweeteners, such as aspartame and neotame, are subject to (Wilk et al., 2022).
Sucralose
Sucralose is an artificial form of the naturally occurring sugar, sucrose (AlDeeb et al., 2013). Most research on sucralose has been metabolic, studying the breakdown of sucralose into other non-toxic components, rather than clinical in animals or humans (A et al., 2000; Grice & Goldsmith, 2000; J et al., 2000; Sg et al., 2000). Over one hundred safety studies have been conducted testing the hydrolysis of sucralose, claiming sucralose is safe to consume in moderate amounts (Grice✠ & Goldsmith, 2000). Researchers found that 85% of sucralose was excreted intact; the other 15% doesn’t interact with biological macromolecules and is biotransformed to biologically/toxicologically insignificant conjugates (Berry et al., 2016). Furthermore, the chemical structure of sucralose contains no structural alerts that give reason that it may promote carcinogenic activity, in part due to its chemical resemblance to sucrose ( Sucralose Non-Carcinogenicity: A Review of the Scientific and Regulatory Rationale , n.d.). Even when exposure levels of sucralose are greatly magnified in rats, sucralose remains non-carcinogenic and safe to consume (Mann et al., 2000).
Advantame
Advantame is a relatively new artificial sweetener. It was approved by the FDA in 2014 and is similar in structure to neotame and aspartame. The few studies available characterizing the malignancy profile of advantame were all conducted on varying mammals (EFSA Panel on Food Additives and Nutrient Sources Added to Food (ANS), 2013; Otabe et al., 2011). Several genotoxicity assays – assays identifying possibly DNA-damaging substances – have been conducted in mice using advantame (EFSA Panel on Food Additives and Nutrient Sources Added to Food (ANS), 2013; Otabe et al., 2011). In the most significant and long-term study, N=384 mice underwent a 104-week dietary test and found no increased rates of tumor development or neoplastic lesions (Otabe et al., 2011). The results of these studies in 2013 proved that advantame is both non-mutagenic and non-genotoxic. Future research should focus on human studies, as advantame is linked structurally to aspartame, which has been found to induce numerous cancers. As advantame continues to remain commercially available, the need for additional research grows.
Conclusion
While studies linking artificial sweeteners to cancer vary, the literature is still rudimentary, with few, high-quality, long-term, human-based studies to thoroughly evaluate the carcinogenic properties of artificial sweeteners. Most studies are small and provide only weak evidence of associations between cancers. As typical in biological research, most of what we know about the associations between artificial sweeteners and cancer risk are derived from animal models. Here, we include human data as available. Future human studies evaluating the association between artificial sweeteners and cancer risk are required. With brands such as such as Splenda , Equal , and Truvia becoming household staples , it is crucial to deepen our understanding of the long-term health implications of artificial sweeteners.
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February was a month full of technological advances and challenges, especially in quantum computing, AI, and cybersecurity.
Amazon’s Ocelot Quantum Chip
With the help of AWS (Amazon Web Services) cloud division, Amazon was able to release its first quantum computing chip, named “Ocelot”. This prototype looks to address challenges in quantum computing, especially correcting errors and scalability. The Ocelot chips uses “cat qubits,” to suppress qubit bit-flip errors, which ultimately reduces the overall errors in quantum systems. This development puts Amazon next to other tech giants like Microsoft and Google, who are also taking big leaps in the quantum computing field.
Microsoft’s Majorana 1 and Google’s Willow Chips
Microsoft released its “Majorana 1” chip, and Google introduced its “Willow” chip, both signaling significant strides in quantum computing. Both chips use quantum physics to process information in a completely new way, underscoring the growing interest and investment in quantum computing from big companies.
Google’s Gemini 2.0 Pro
Google made AI advancements following the release of Gemini 2.0 Pro, which introduces even more AI benefits, including enhanced capabilities and user experiences. This update brings a larger context window, allowing over 1 million tokens to be processed at once, making it highly efficient. The Gemini mobile app now includes Deep Research, a features that allows users to go deeper into topics with AI assistance, summarizing research papers, and generating insights almost immediately. Gemini 2.0 Pro is also able to analyze text, images, and even videos.
Cybersecurity Concerns
With AI models gaining more power, many concerns regarding security and data are rising. Reports show that almost 45% of AI breaches in the past year are coming from malware in public models. Also, government agencies are now facing scrutiny over how AI systems access and store private data. As AI becomes used more in daily life, it’s necessary to balance innovation with security.
February was a transformative month for technology, and I’m sure there will be many more advancements in the next month.
Resources:
Nellis, Stephen. “Amazon Unveils Quantum Chip, Aiming to Shave Years off Development Time.” Arizona Digital Free Press, 3 Mar. 2025, arizonadigitalfreepress.com/amazon-unveils-quantum-chip-aiming-to-shave-years-off-development-time/.
19, Written by Catherine Bolgar Published February, et al. “Microsoft’s Majorana 1 Chip Carves New Path for Quantum Computing.” Microsoft, 19 Feb. 2025, news.microsoft.com/source/features/innovation/microsofts-majorana-1-chip-carves-new-path-for-quantum-computing/.
Sekhon, Gianetan Singh. “Microsoft Majorana 1 vs Google Willow.” Medium, Medium, 25 Feb. 2025, medium.com/@gianetan/microsoft-majorana-1-vs-google-willow-0c000c098007.
“Gemini 2.0 Pro.” Google DeepMind, deepmind.google/technologies/gemini/pro/. Accessed 4 Mar. 2025.
Michelle Moore, PhD. “Top Cybersecurity Threats [2025].” University of San Diego Online Degrees, 23 Jan. 2025, onlinedegrees.sandiego.edu/top-cyber-security-threats/.
Artificial Intelligence (AI) is transforming almost every single aspect of our lives, and biology is no exception. Recently, AI has played a major role in discoveries regarding genomics (study of genes) and personalized treatments and medications for patients. These advancements are altering how doctors are treating diseases, and changing our understanding of DNA.
AI in Genomics
The human genome is very complex, and sequencing it creates large amounts of data. However, with the help of AI, the process is sped up. Artificial intelligence’s ability to process large amount of data quickly, is assisting scientists in sorting this data and collecting information.
Machine learning, a type of AI, is probably the most useful tool in medicine, because it has the ability to analyze gene sequences and find patterns that would normally go unnoticed. For example, AI is being used for looking at gene mutations to predict how it could lead to diseases like cancer or heart disease. By identifying these genetic markers early-on, AI can allow doctors diagnose patients earlier, and help scientists discover ways to treat or even prevent these diseases.
AI is drastically speeding up research and making it easier to understand the complexity that is genetics, opening doors to major medical breakthroughs.
Personalized Medicine
Medicine is personalized to make sure treatments align with everyone’s unique genetic makeup, rather than using generic treatments for everyone. This is where AI is making a big difference. By looking at patient’s genetic information and medical history, AI is able to help doctors decide which treatment works best for an individual.
For example, if someone has cancer, AI can help doctors choose the best chemotherapy drugs based on that person’s unique genetic mutations, something we were unable to do before. AI is also helping scientists develop new tests and treatments, customized for individual patients, which can lead to better outcomes and fewer side effects.
Ultimately, AI is helping doctors get to know each patient’s DNA and create more personalized healthcare at an unprecedented rate. It’s a major leap forward compared to the old “one-size-fits-all” treatments.
Challenges and Ethics
Although AI is doing amazing things in biology, it is not all smooth sailing. There are a few challenges and ethical concerns that must be addressed. For one, the privacy regarding genetic data is a major concern. If AI is analyzing personal genetic information, how do we make sure that this data is kept safe from hackers or misuse?
Additionally, there are big ethical questions around the extent as to how AI should be used in genetics. For example, how far should we go when it comes to editing genes or predicting someone’s future health? Should we even be allowed to change someone’s genes before they are born? These are all questions scientists and ethicists are trying to figure out.
Even with these challenges, the potential for AI is huge, especially in biology. It’s already making an impact, and it will definitely continue to change the future of medicine.
AI is the Future ofMedicine
AI is not just a cool futuristic idea—it’s already changing the way we study genetics and treat diseases. By helping scientists unlock the mysteries of our DNA and provide more personalized medicine and treatments, AI is making healthcare more effective than ever. As technology advances and more breakthroughs are made, we can expect AI to play an even bigger role in healthcare, ultimately leading to a future where treatments are better tailored to each individual.
Resources Used:
Vilhekar, Rohit S, and Alka Rawekar. “Artificial Intelligence in Genetics.” Cureus vol. 16,1 e52035. 10 Jan. 2024, doi:10.7759/cureus.52035
Costa, Katrina. “Ai and Genome Engineering: New Directions in Biology.” Wellcome Sanger Institute Blog, 18 Dec. 2024, sangerinstitute.blog/2024/10/24/ai-and-genome-engineering-new-directions-in-biology/.
Johnson, Kevin B, et al. “Precision Medicine, AI, and the Future of Personalized Health Care.” Clinical and Translational Science, U.S. National Library of Medicine, Jan. 2021, pmc.ncbi.nlm.nih.gov/articles/PMC7877825/#:~:text=Precision%20medicine%20methods%20identify%20phenotypes,decision%20making%20through%20augmented%20intelligence.
Farhud, Dariush D, and Shaghayegh Zokaei. “Ethical Issues of Artificial Intelligence in Medicine and Healthcare.” Iranian Journal of Public Health, U.S. National Library of Medicine, Nov. 2021, pmc.ncbi.nlm.nih.gov/articles/PMC8826344/.
Recently, I’ve successfully been able to download DeepSeek R1, an AI-powered tool, on my computer using llama.cpp. DeepSeek has been making major advancements in the world of search and language models. Installing it on my computer came with a few bumps, however with this post, you’ll be able to easily download it on your device. Since downloading it, I’ve been able to experiment with its various tools. At the end of the day, it’s interesting to see how artificial intelligence is growing, and I’m excited to explore this model more.
Steps to Download DeepSeek R1 on Your MacBook
Install the Needed Packages
Open Terminal: cmd & space, search Terminal, press Enter
Artificial Intelligence (AI) has evolved from a theoretical concept to a powerful source. As the new year begins, the big question is not only how far AI has come, but also where it’s headed.
Quantum AI: The Next Frontier
One of the most groundbreaking changes expected this year is Quantum AI. Quantum computers use the strange principles of quantum mechanics to process data in ways that traditional computers simple can’t. In the real-world, this means being able to train AI faster than ever, meaning drug discoveries in days, not years. Another asset to quantum AI is being able to solve impossible problems like optimizing global supply chains or tackling climate change models in real time.
AI vs. Climate Change
In 2025, AI will be in the frontlines in the fight against climate change. This year, we can expect AI to be able to predict extreme weather with absurd precision, helping prepare for hurricanes, floods, and droughts. With AI’s help, we can revolutionize farming by using algorithms to maximize crop yields while cutting water and fertilizer use. To combat power waste, AI can optimize power by creating smarter grids to make renewable energy more reliable.
AI In Healthcare
As we’ve seen in previous years, AI is revolutionizing the medical feild, and we can expect even more advancements this year. AI in healthcare isn’t just about robots in surgery (althought that sounds very cool). In the next 12 months, we’ll see AI discovering new drugs and diagnoses in groundbreaking time. Wearable tech powered by AI will allow you to be alerted of risks before they become emergencies.
AI in Creativity
AI isn’t just crunching numbers, it’s also transforming creativity. We’ve already seen AI generated art and music, but 2025 will push the boundaries even further. Writers, filmmakers, and game designers will be able to use AI to bring their ideas to life faster than ever. Imagine NPCs in your video games that react to your every move in ways that a human would or films generated by AI that adapt to the audience’s preferences in real time.
AI-Powered Learning
Eearning is getting a major glow-up. Using AI, students will be able to tailor their learning experiences, making lessons more engaging. AI translation tools will be more accessible, allowing education to be accessible worldwide and breaking language barriers. And, if you ever need help with math at 2 a.m., don’t worry, AI will help you with their vitual tutors.
AI vs. Hackers
As cyber threats become more sophisticated, AI is stepping up to defend against them. AI will be able to stop cyberattacks before they even happen by using real-time threat detections. Banks will use AI to detect fradulent transactions instantly, provididing stronger protetion against financial crimes. In 2025, AI won’t just help us work smarter – it’ll keep us safer.
