Life
AI Decodes the Language of DNA: Revolutionising Genomics and Personalised Medicine
AI decodes DNA, revolutionising genomics and personalised medicine with GROVER.
TL;DR:
- AI language model GROVER decodes DNA as a language, revealing hidden genetic functions.
- GROVER identifies gene promoters, protein binding sites, and epigenetic information.
- This breakthrough could revolutionise genomics and personalised medicine.
Imagine if you could read the language of life itself. That’s precisely what researchers have achieved with GROVER, an AI language model trained on human DNA. This innovative approach treats DNA as a language, learning its rules and context to extract biological meanings, such as gene promoters and protein binding sites. This breakthrough could revolutionise genomics and personalised medicine by unlocking hidden layers of genetic information.
Understanding DNA as a Language
DNA contains the foundational information needed to sustain life. Understanding how this information is stored and organised has been one of the greatest scientific challenges of the last century. With GROVER, a new large language model trained on human DNA, researchers could now attempt to decode the complex information hidden in our genome.
Developed by a team at the Biotechnology Center (BIOTEC) of Dresden University of Technology, GROVER treats human DNA as a text, learning its rules and context to draw functional information about the DNA sequences. This new tool, published in Nature Machine Intelligence, has the potential to transform genomics and accelerate personalised medicine.
The Complexity of DNA
Since the discovery of the double helix, scientists have sought to understand the information encoded in DNA. 70 years later, it is clear that the information hidden in the DNA is multilayered. Only 1-2% of the genome consists of genes, the sequences that code for proteins.
“DNA has many functions beyond coding for proteins. Some sequences regulate genes, others serve structural purposes, most sequences serve multiple functions at once. Currently, we don’t understand the meaning of most of the DNA,” says Dr. Anna Poetsch, research group leader at the BIOTEC.
AI and Large Language Models
Large language models, like GPT, have transformed our understanding of language. Trained exclusively on text, these models have developed the ability to use language in many contexts.
“DNA is the code of life. Why not treat it like a language?” says Dr. Poetsch.
The Poetsch team trained a large language model on a reference human genome. The resulting tool named GROVER, or “Genome Rules Obtained via Extracted Representations”, can be used to extract biological meaning from the DNA.
“GROVER learned the rules of DNA. In terms of language, we are talking about grammar, syntax, and semantics. For DNA this means learning the rules governing the sequences, the order of the nucleotides and sequences, and the meaning of the sequences. Like GPT models learning human languages, GROVER has basically learned how to ‘speak’ DNA,” explains Dr. Melissa Sanabria, the researcher behind the project.
The DNA Dictionary
“DNA resembles language. It has four letters that build sequences and the sequences carry a meaning. However, unlike a language, DNA has no defined words,” says Dr. Poetsch.
DNA consists of four letters (A, T, G, and C) and genes, but there are no predefined sequences of different lengths that combine to build genes or other meaningful sequences.
To train GROVER, the team had to first create a DNA dictionary. They used a trick from compression algorithms.
“This step is crucial and sets our DNA language model apart from the previous attempts,” says Dr. Poetsch.
“We analysed the whole genome and looked for combinations of letters that occur most often. We started with two letters and went over the DNA, again and again, to build it up to the most common multi-letter combinations.
“In this way, in about 600 cycles, we have fragmented the DNA into ‘words’ that let GROVER perform the best when it comes to predicting the next sequence,” explains Dr. Sanabria.
The Promise of AI in Genomics
GROVER promises to unlock the different layers of genetic code. DNA holds key information on what makes us human, our disease predispositions, and our responses to treatments.
“We believe that understanding the rules of DNA through a language model is going to help us uncover the depths of biological meaning hidden in the DNA, advancing both genomics and personalised medicine,” says Dr. Poetsch.
Potential Applications
GROVER has the potential to advance genomics and personalised medicine, offering insights into human biology and disease. The model identifies gene promoters, protein binding sites, and epigenetic information, enhancing understanding of DNA’s non-coding regions.
DNA language model GROVER learns sequence context in the human genome. Deep-learning models that learn a sense of language on DNA have achieved a high level of performance on genome biological tasks. Genome sequences follow rules similar to natural language but are distinct in the absence of a concept of words.
The defined dictionary of tokens in the human genome carries best the information content for GROVER. Analysing learned representations, we observed that trained token embeddings primarily encode information related to frequency, sequence content and length.
Some tokens are primarily localised in repeats, whereas the majority widely distribute over the genome. GROVER also learns context and lexical ambiguity. Average trained embeddings of genomic regions relate to functional genomics annotation and thus indicate learning of these structures purely from the contextual relationships of tokens.
This highlights the extent of information content encoded by the sequence that can be grasped by GROVER.
On fine-tuning tasks addressing genome biology with questions of genome element identification and protein–DNA binding, GROVER exceeds other models’ performance. GROVER learns sequence context, a sense for structure and language rules. Extracting this knowledge can be used to compose a grammar book for the code of life.
Concluding Thoughts: The Future of Genomics
The development of GROVER marks a significant milestone in the field of genomics. By treating DNA as a language, AI models can uncover hidden layers of genetic information, offering new insights into disease predispositions and treatments. This breakthrough could revolutionise personalised medicine, providing tailored treatments based on an individual’s genetic makeup.
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What do you think about the potential of AI in decoding the language of DNA? How do you see this technology impacting the future of personalised medicine? Share your thoughts and experiences in the comments below. Don’t forget to subscribe for updates on AI and AGI developments.
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Where Can You Apply Generative vs. Analytical AI Effectively?
This article explores AI business strategies, focusing on the differences between generative and analytical AI and how to balance their use for maximum impact.
TL;DR
- Generative AI excels in content creation, mimicking human output, and enhancing productivity, but it comes with higher risks and uncertainties.
- Analytical AI is ideal for predictive tasks, decision-making, and risk management, offering more measurable benefits and lower risks.
- Companies should balance their AI strategies based on their business models, data types, and risk tolerance, with many use cases combining both approaches.
Understanding Generative and Analytical AI
Organisations are increasingly faced with a choice: generative AI or analytical AI? While both offer transformative potential, understanding their distinct capabilities, benefits, and risks is crucial for businesses to make informed decisions. This article delves into the differences between these two AI approaches and provides guidance on when to prioritise each, helping organisations maximise their AI investments.
Different Purposes and Capabilities
Generative AI and analytical AI serve different purposes and have unique capabilities. Generative AI, utilising deep learning neural networks, creates new content such as images, text, music, or code, mimicking human creativity. In contrast, analytical AI employs statistical machine learning for specific tasks like classification, prediction, or decision-making based on structured data.
For instance, in a marketing campaign, analytical AI can determine which product to promote to which customer, while generative AI can craft the personalised language and images for the promotion.
Different Algorithmic Methods
Generative AI often employs complex techniques like transformers, attention mechanisms, generative adversarial networks (GANs), and variational autoencoders (VAEs) to generate content. These models learn patterns in data to create new instances, typically requiring extensive computational resources and vast amounts of data.
Analytical AI, on the other hand, utilises simpler machine learning approaches such as supervised learning, unsupervised learning, and reinforcement learning. Models are usually trained on past data and applied to real-world situations by companies using their own data.
Different Types of Data
Generative AI uses unstructured data formats like text, images, and sequences to predict other sequences. Analytical AI, however, employs structured data—typically rows and columns of numbers—with supervised learning requiring data with known and labelled outcomes.
Different Returns on Investment
Generative AI can yield cost savings from increased productivity in content generation and higher customer engagement through personalised content. However, its economic value can be challenging to measure and often requires training on a company’s specific content, increasing costs.
Analytical AI provides better economic returns through predictive models that help businesses forecast demand, optimise inventory, identify market trends, and make data-driven decisions. It can also analyse customer data to tailor marketing campaigns, create product recommendations, and deliver personalised customer experiences, leading to higher customer satisfaction and loyalty.
Balancing Risks and Benefits
Security Concerns
Generative AI poses risks such as deepfakes, intellectual property infringement, and privacy concerns from sensitive information in training data. Analytical AI faces risks from cybersecurity breaches, biased datasets, and potential misuse for malicious purposes.
Measuring Economic Value
The benefits of analytical AI are often easier to measure than generative AI because they are captured in transactional systems, customer purchases, and costs. Both AI types can provide significant ROI through increased efficiency, productivity, innovation, and customer satisfaction, depending on the specific use case and industry.
Striking the Right Balance
Consider Your Strategy and Business Model
Companies should prioritise generative AI if their primary business involves creating, selling, or distributing content. For instance, Bristol Myers Squibb uses generative AI for creating novel content in computational biology, while Universal Music leverages it for music creation and imitating artist voices.
Evaluate Your Data Assets
If a company’s data assets are primarily unstructured content like text, images, or video, generative AI should take precedence. Conversely, if most of the data is structured and numerical, analytical AI should be the focus.
Assess Risk Tolerance
Generative AI is considered riskier, with higher benefit uncertainty. Companies should evaluate their risk tolerance and willingness to accept these uncertainties when deciding their AI focus.
Democratising AI
Generative AI helps democratise access to advanced tools, making AI capabilities more accessible to non-technical users. This shift is crucial for fostering innovation and improving decision-making across organisations.
Join the Conversation
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Make 2025 Your Most Productive Year Yet by Using AI to Get Started
Explore 12 AI tools for productivity, including language learning, budget tracking, health apps, and more, to make 2025 your most efficient year in Asia.
TL;DR:
- AI tools can significantly enhance productivity and daily life in Asia.
- Top tools include Google Translate, Duolingo, Google Assistant, Siri, Wally, Spendee, Grammarly, Fitbit, Apple Health, Google Photos, Canva, MyFitnessPal, Feedly, ShopSavvy, Citymapper, and Snapseed.
- Integrating these tools can lead to better organisation, improved skills, and healthier habits.
A New Year, New Abilities?
As 2025 approaches, why not make use of some clever AI tools to enhance day-to-day living? Whether it’s learning a language, managing your budget, or just getting through the day with a little more ease, AI can be surprisingly helpful. Here’s a friendly guide with 12 beginner-friendly AI tools, each perfect for small, practical improvements to start your year right!
1. Pick Up a New Language or Just Get Around Easier with Translation Tools
Having a translation tool is crucial if you are living in Asia or travelling there. Google Translate is a classic choice—not just for typing in words, but for translating menus, signs, and even whole documents on the spot. Use the camera feature to hover over text, and Google Translate gives you an instant translation right there. Perfect for those “oh no, what did I just order?” moments!
If you are prepared to go a little further, Duolingo makes learning a language’s foundations enjoyable and manageable. With daily goals and streaks, it’s a little routine you can build into each day, and before you know it, you’ll have a nice base in your chosen language.
Tool Links:
Quick Tips:
- Try camera mode on Google Translate for real-time translations of signs and menus—super helpful for those little surprises in new places!
- Download language packs in Google Translate for offline use, which is a lifesaver when Wi-Fi’s not around.
- Set a five-minute daily goal on Duolingo and do it while commuting or during a coffee break. Those minutes add up, and it’s an easy habit to keep up.
2. Organise Your Day with Google Assistant or Siri
Ever wish you had a personal assistant? Turns out, you kind of do—right in your phone. Google Assistant and Siri are perfect for staying on top of everyday tasks without even lifting a finger. Just ask Siri or Google to remind you about a meeting, set timers, or add items to your shopping list.
Imagine starting your day with “Hey Siri, what’s on my schedule today?” or “Hey Google, remind me to check the train schedule at 8 a.m.” You’ll always be one step ahead and save yourself from forgetting the little things.
Tool Links:
Quick Tips:
- Set up a ‘Good Morning’ routine to get a rundown of your day, traffic, and the weather—one less thing to think about.
- Use location-based reminders like, “remind me to buy groceries when I leave work.” Siri and Google Assistant will keep you on track without lifting a finger.
- Try voice commands for cooking or driving to make life hands-free, from setting timers to searching for quick answers.
3. Track Your Spending and Savings Goals with Wally or Spendee
Budgets can be tricky, especially in Asia’s lively cities, where there’s always a great food spot or unique shop to tempt you. That’s where Wally and Spendee come in. These apps help you track expenses, set budgets, and even set goals—whether that’s saving up for a holiday or managing those day-to-day splurges. You’ll get visual breakdowns of your spending, so you can see where your money’s going without any complicated spreadsheets.
And the best part? Some of these apps even give you live currency conversion, which is a lifesaver if you’re switching currencies while travelling or living abroad.
Tool Links:
Quick Tips:
- Start with tracking one category, like dining out, to see patterns and adjust. It’s an easy way to ease into budgeting.
- Set a small savings goal for something you’re excited about—a weekend trip or a new gadget. Seeing progress towards a goal can make budgeting more motivating.
- Use currency conversion features when travelling to avoid surprises—perfect for making sure your budget’s on track abroad!
4. Improve Your Writing with Grammarly
Ever wished you had an extra set of eyes on your emails or posts? Grammarly is like a writing coach in your browser. It checks for grammar, spelling, and even the tone of your writing. Grammarly is a lifesaver if you’re sending out work emails or trying to nail a professional message, ensuring your words sound just as polished as you intended.
It’s a simple browser extension, so you can use it everywhere—from social media posts to important reports—and get feedback instantly. And if English isn’t your first language, Grammarly can be a great confidence boost.
Tool Link:
Quick Tips:
- Set tone preferences in Grammarly to get advice that matches what you’re aiming for, like casual or professional.
- Use Grammarly for emails to make sure your messages sound clear and polished, especially when sending them off quickly.
- Enable Grammarly’s browser extension for real-time feedback across email, documents, and social media.
5. Keep Fit and Healthy with Fitbit or Apple Health
Staying active in Asia’s bustling cities can be a challenge, but apps like Fitbit and Apple Health make it easy to track your wellness goals. With these apps, you can set daily step targets, track sleep, and even keep an eye on your heart rate trends. They give you reminders to move or drink water, so even with a busy schedule, you can build small wellness habits.
Set daily goals to keep things manageable—maybe a step count to reach or a sleep goal to aim for. And by the end of the month, you can see exactly how those little changes have added up.
Tool Links:
Quick Tips:
- Start with a simple step count goal (e.g., 5,000 steps) and gradually increase. You’ll start noticing improvements in your energy.
- Use the water tracker feature to stay hydrated, which is especially helpful in hot, humid climates.
- Check your sleep trends to see if there are any small changes that can improve sleep quality, like reducing screen time before bed.
6. Keep Your Photos Organised with Google Photos
Asia is full of scenic spots, so if your photo library is starting to look a bit chaotic, Google Photos has you covered. This app uses AI to automatically organise your pictures by location, people, and even objects. It’s perfect for finding specific photos without endless scrolling, like that beach sunset in Bali or street food tour in Bangkok.
Google Photos also suggests albums, montages, and even short videos, so you can relive your favourite memories without putting in hours of editing.
Tool Link:
Quick Tips:
- Enable location tagging so Google Photos can automatically organise by place.
- Create shared albums with friends and family for group trips and events, so everyone can add their best shots.
- Use the search bar for keywords like “beach” or “birthday” to find specific photos instantly.
7. Create Stunning Visuals with Canva
Need to design social media posts, invitations, or presentations? Canva makes graphic design easy with ready-to-use templates. You don’t need any design experience—just pick a template, drop in your content, and Canva’s AI will suggest colours and layouts that look polished.
Whether you’re working on a project for work or just want to make a birthday card, Canva has tools to help you create something that looks like it took way more effort than it actually did!
Tool Link:
Quick Tips:
- Start with templates based on what you’re making (e.g., “Instagram post” or “poster”) for ideas on layout and style.
- Use Canva’s resize feature to adapt your design for multiple platforms, saving you tons of time if you’re posting on social media.
- Check out Canva’s free elements like icons, stock photos, and fonts to add unique touches to your designs.
8. Plan Healthy Meals and Track Nutrition with MyFitnessPal
Keeping up with healthy eating can be tricky when you’re juggling work, family, and social life. MyFitnessPal helps by tracking your meals, exercise, and even water intake. Just log what you eat, and MyFitnessPal breaks down your nutrients, helping you see what you’re doing well and where you could use a little improvement.
Whether you’re looking to maintain, gain, or lose weight, this app adjusts suggestions based on your goals, making it easy to fit healthy habits into your lifestyle.
Tool Link:
Quick Tips:
- Log meals right after eating to keep track without it feeling like a chore.
- Use MyFitnessPal’s barcode scanner to log foods instantly and get accurate nutritional info.
- Review your weekly nutrition breakdown to see trends and adjust—small tweaks add up over time.
9. Stay Updated on News and Trends with Feedly
If keeping up with industry news or global trends is part of your routine, Feedly can be a game-changer. This AI-powered app organises articles and blog posts into a personalised feed, helping you stay informed without the endless scrolling. It’s ideal for professionals across Asia who want a quick, organised way to catch up on tech, business, or even local events.
Tool Link:
Quick Tips:
- Set up feeds based on specific interests, like “Asia tech news” or “digital marketing,” so you only see the most relevant articles.
- Use Feedly’s ‘Read Later’ feature to save longer reads for a commute or break.
- Follow industry leaders or popular publications within Feedly to get curated insights straight from the source.
10. Make Smarter Shopping Decisions with ShopSavvy
If you’re a frequent shopper, ShopSavvy can help you find the best deals by comparing prices across different retailers. Just scan a product barcode, and ShopSavvy shows you prices from nearby stores or online platforms. It’s great for spotting deals or deciding if it’s worth buying locally or online.
Tool Link:
Quick Tips:
- Use ShopSavvy to compare prices before buying electronics, clothing, or big-ticket items.
- Check for coupons or deals within the app to potentially save even more on your purchase.
- Enable location settings to get alerts on deals nearby while you’re out shopping.
11. Manage Daily Commutes and Travel with Citymapper
For those navigating large cities or travelling frequently in Asia, Citymapper is a fantastic app that simplifies commutes. It offers AI-driven route planning that combines buses, trains, subways, and walking options, so you can find the quickest or cheapest way to get around. It’s especially helpful in cities with extensive public transport systems like Tokyo, Singapore, or Hong Kong.
Tool Link:
Quick Tips:
- Save favourite routes to quickly access your usual commute times and updates.
- Enable push notifications to get live updates on delays or alternative routes during your journey.
- Use Citymapper’s “Nearby” feature to find transit stops, bikes, or scooters near you for a last-minute commute option.
12. Create Fun and Unique Photo Edits with Snapseed
If you enjoy capturing memories or exploring Asia’s scenic spots, Snapseed is a fantastic app to enhance your photos. Created by Google, Snapseed offers a range of AI-powered editing tools that make your images look professional with just a few taps. You can adjust lighting, add filters, blur backgrounds, and even remove unwanted objects from the photo—all from your phone.
Tool Link:
Quick Tips:
- Use the “Selective” tool to adjust brightness or contrast in specific parts of the photo, which is great for enhancing details without changing the whole image.
- Experiment with the “Lens Blur” effect for a soft background blur, making your subject stand out—ideal for food photos or portraits.
- Try the “Healing” tool to remove small distractions, like a stray object in the background, to keep the focus on your subject.
Small Steps, Big Wins in 2025
Start with one or two of these tools, and see how they fit into your routine. Each one offers small, simple improvements that can make a big difference over time. So pick a tool, set a small goal, and start exploring how AI can make life just that bit easier in 2025.
Here’s to a smooth, productive year!
Join the Conversation:
What AI tools have you found most helpful in your daily life? Share your experiences and tips with our community below! Don’t forget to subscribe for updates on AI and AGI developments here.
You may also enjoy our AI Unleashed series, which offers a hands on comparison and overview of the most popular AI apps:
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OpenAI’s Bold Venture: Crafting the Moral Compass of AI
OpenAI funds moral AI research at Duke University to align AI systems with human ethical considerations.
TL;DR
- OpenAI funds a $1 million, three-year research project at Duke University to develop algorithms that predict human moral judgements.
- The project aims to align AI systems with human ethical considerations, focusing on medical ethics, legal decisions, and business conflicts.
- Technical limitations, such as algorithmic complexity and data biases, pose significant challenges to creating moral AI.
The quest to imbue machines with a moral AI compass is gaining momentum.
OpenAI, a leading AI research organisation, has taken a significant step in this direction by funding a $1 million, three-year research project at Duke University. Led by practical ethics professor Walter Sinnott-Armstrong, this initiative aims to develop algorithms capable of predicting human moral judgements in complex scenarios.
As AI continues to permeate various aspects of our lives, the need for ethically aware systems has never been more pressing.
The AI Morality Project at Duke University
The AI Morality Project at Duke University, funded by OpenAI, is a groundbreaking initiative focused on aligning AI systems with human ethical considerations. This three-year research project, led by Walter Sinnott-Armstrong, aims to create algorithms that can predict human moral judgements in intricate situations such as medical ethics, legal decisions, and business conflicts.
While specific details about the research remain undisclosed, the project is part of a larger $1 million grant awarded to Duke professors studying “making moral AI.” The research is set to conclude in 2025 and forms part of OpenAI’s broader efforts to ensure that AI systems are ethically aligned with human values.
Research Objectives and Challenges
The OpenAI-funded research at Duke University aims to develop algorithms capable of predicting human moral judgements, addressing the complex challenge of aligning AI decision-making with human ethical considerations. This ambitious project faces several key objectives and challenges:
- Developing a robust framework for AI to understand and interpret diverse moral scenarios: AI systems need to comprehend and analyse various ethical situations to make informed decisions.
- Addressing potential biases in ethical decision-making algorithms: Ensuring that AI systems are free from biases is crucial for fair and just decision-making.
- Ensuring the AI can adapt to evolving societal norms and cultural differences in moral judgements: AI systems must be flexible enough to adapt to changing societal norms and cultural variations.
- Balancing the need for consistent ethical reasoning with the flexibility to handle nuanced situations: AI must strike a balance between consistent ethical reasoning and the ability to handle complex, nuanced scenarios.
While the specific methodologies remain undisclosed, the research likely involves analysing large datasets of human moral judgements to identify patterns and principles that can be translated into algorithmic form. The project’s success could have far-reaching implications for AI applications in fields such as healthcare, law, and business, where ethical decision-making is crucial.
Technical Limitations of Moral AI
While the pursuit of moral AI is ambitious, it faces significant technical limitations that challenge its implementation and effectiveness:
- Algorithmic complexity: Developing algorithms capable of accurately predicting human moral judgments across diverse scenarios is extremely challenging, given the nuanced and context-dependent nature of ethical decision-making.
- Data limitations: The quality and quantity of training data available for moral judgments may be insufficient or biased, potentially leading to skewed or inconsistent ethical predictions.
- Interpretability issues: As AI systems become more complex, understanding and explaining their moral reasoning processes becomes increasingly difficult, raising concerns about transparency and accountability in ethical decision-making.
These technical hurdles underscore the complexity of creating AI systems that can reliably navigate the intricacies of human morality, highlighting the need for continued research and innovation in this field.
Ethical AI Foundations
AI ethics draws heavily from philosophical traditions, particularly moral philosophy and ethics. The field grapples with fundamental questions about the nature of intelligence, consciousness, and moral agency. Key philosophical considerations in AI ethics include:
- Moral status: Determining whether AI systems can possess moral worth or be considered moral patients.
- Ethical frameworks: Applying and adapting existing philosophical approaches like utilitarianism, deontology, and virtue ethics to AI decision-making.
- Human-AI interaction: Exploring the ethical implications of AI’s increasing role in society and its potential impact on human autonomy and dignity.
- Transparency and explainability: Addressing the philosophical challenges of creating AI systems whose decision-making processes are comprehensible to humans.
These philosophical enquiries form the foundation for developing ethical guidelines and principles in AI development, aiming to ensure that AI systems align with human values and promote societal well-being.
Final Thoughts: The Path Forward
The AI Morality Project at Duke University, funded by OpenAI, represents a significant step towards creating ethically aware AI systems. While the project faces numerous challenges, its potential to influence the development of moral AI in various fields is immense. As AI continues to integrate into our daily lives, ensuring that these systems are aligned with human ethical considerations is crucial for a harmonious and just future.
Join the Conversation:
What are your thoughts on the future of moral AI? How do you envisage AI systems making ethical decisions in complex scenarios? Share your insights and experiences with AI technologies in the comments below.
Don’t forget to subscribe for updates on AI and AGI developments here. Let’s keep the conversation going and build a community of tech enthusiasts passionate about the future of AI!
You may also like:
- Mastering AI Ethics: Your Guide to Responsible Innovation
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- How AI is Becoming More Reliable and Transparent
- Or try Google Gemini for free by tapping here.
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