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ChatGPT was released in June 2020 and it is developed by OpenAI. It has led to revolutionary developments in many areas. One of these areas is the creation of database queries.The database queries can be generated from plain text via . It helps you with databases that you have little knowledge about. ChatGPT Artificial intelligence, which has progressively integrated into our daily lives, has gained significant momentum with the rise of ChatGPT. Before moving into the project, let’s briefly explore ChatGPT. To fully comprehend the capabilities of ChatGPT, it is essential to have a solid grasp of its underlying architecture. ChatGPT has been developed based on the architecture. So let’s take a look at transformers first. GPT For direct access to the project, click . here Transformers utilize seq2seq frameworks, enabling the conversion of one sequence into another. The sequences have defined ordering. As an illustration, sentences can be viewed as a succession of words. The Transformers can also be used to solve NLP such as text translation. We need a lot of labeled data for training this architecture. This would be difficult for transformers to learn. We can use transfer learning to solve this problem. Transformers consist of two components (Fig 1): an encoder and a decoder, both adept at acquiring a proficient language representation. This proficiency allows us to construct language models from each component. By stacking the encoders, we obtain a idirectional ncoder epresentation of ransformers, commonly known as . Similarly, by stacking the decoder units, we can achieve enerative re- raining that is GPT. In the our case we are focusing on GPT. Let’s think about transfer learning in the context of GPT. When we train a model from scratch, it typically demands a substantial amount of data as the parameters are initially set randomly. However, imagine a scenario where the parameters fortuitously align with the values we require. In such cases, we don’t necessitate an extensive dataset to attain our desired outcome. As will be understood, BERT and GPT are used in transfer learning concept. B E R T BERT G P T The GPT training is thus divided into two parts. We have pre-training part where we train the GPT architecture to understand what language is and then fine tuning part where we use transfer learning to further train the GPT architecture to perform well on specific language tasks GPT has a structure that takes random word sequences as input and predicts the next most suitable word. Sample prediction can be seen at Fig 2. Language modeling is selected as an ideal foundation for understanding the fundamental aspects of language and can be readily fine-tuned. It is commonly known as a self-supervised task since the sentences themselves serve as both input and output labels. Let’s move on to ChatGPT. As it can be seen in Fig 3., the entire ChatGPT process can be divided into three major steps. In the first step, GPT model is used that has been pre-trained on understanding language itself. The next step involves fine-tuning the model to effectively process user prompts and generate appropriate responses based on those prompts. To facilitate this process, labeled data is obtained by engaging labelers who not only provide prompts but also specify the desired response for each prompt. This allows for engaging in supervised fine-tuning of the GPT model, as there are both input prompts and corresponding output responses. In the next step, the supervised fine-tuned model is used that it was obtained from first step. A single prompt is passed through the model, and multiple responses are generated. The labeler then evaluates and ranks the quality of these responses. Each generated response is assigned a corresponding reward, which is utilized to train another GPT model known as the rewards model. Being a model itself, the rewards model functions by taking an initial prompt and one of the responses as input and generating a reward as output. This reward quantifies the quality or goodness of the response. In the third step, an unseen prompt will be taken and passed through a replica of the supervised fine-tuned model. This will generate a response, which will then be evaluated using a rewards model to determine its rank or quality. The rank obtained will be used to further refine our already fine-tuned model. This is achieved by incorporating the rank into the loss function of the PPO model, allowing updates to the model’s parameters through backpropagation. What’s particularly fascinating is that this process not only helps the model exhibit non-toxic behavior but also enables it to generate factual responses. This is because the reward itself was generated based on the quality of the response. ChatSQL Now let’s make a project with ChatGPT using python. LangChain framework is used for this project. Our objective is to retrieve information from our database using plain text. In our work, we utilized MySQL as the target database. Nevertheless, this approach can also be used to generate queries on other databases. The sample database is shown below. ( All codes can be found here https://github.com/ademakdogan/ChatSQL ) +-----+--------------------------------------------------------+------------------------+-------------------+--------+------------------+
| ID  | Title                                                  | Author                 | Genre             | Height | Publisher        |
+-----+--------------------------------------------------------+------------------------+-------------------+--------+------------------+
|   1 | Fundamentals of Wavelets                               | Goswami, Jaideva       | signal_processing |    228 | Wiley            |
|   2 | Data Smart                                             | Foreman, John          | data_science      |    235 | Wiley            |
|   3 | God Created the Integers                               | Hawking, Stephen       | mathematics       |    197 | Penguin          |
|   4 | Superfreakonomics                                      | Dubner, Stephen        | economics         |    179 | HarperCollins    |
|   5 | Orientalism                                            | Said, Edward           | history           |    197 | Penguin          |
|   6 | Nature of Statistical Learning Theory, The             | Vapnik, Vladimir       | data_science      |    230 | Springer         |
|   7 | Integration of the Indian States                       | Menon, V P             | history           |    217 | Orient Blackswan |
|   8 | Drunkard's Walk, The                                   | Mlodinow, Leonard      | science           |    197 | Penguin          |
|   9 | Image Processing & Mathematical Morphology             | Shih, Frank            | signal_processing |    241 | CRC              |
|  10 | How to Think Like Sherlock Holmes                      | Konnikova, Maria       | psychology        |    240 | Penguin          |
|  11 | Data Scientists at Work                                | Sebastian Gutierrez    | data_science      |    230 | Apress           |
|  12 | Slaughterhouse Five                                    | Vonnegut, Kurt         | fiction           |    198 | Random House     |
|  13 | Birth of a Theorem                                     | Villani, Cedric        | mathematics       |    234 | Bodley Head      |
|  14 | Structure & Interpretation of Computer Programs        | Sussman, Gerald        | computer_science  |    240 | MIT Press        |
|  15 | Age of Wrath, The                                      | Eraly, Abraham         | history           |    238 | Penguin          |
|  16 | Trial, The                                             | Kafka, Frank           | fiction           |    198 | Random House     |
|  17 | Statistical Decision Theory'                           | Pratt, John            | data_science      |    236 | MIT Press        |
|  18 | Data Mining Handbook                                   | Nisbet, Robert         | data_science      |    242 | Apress           |
|  19 | New Machiavelli, The                                   | Wells, H. G.           | fiction           |    180 | Penguin          |
|  20 | Physics & Philosophy                                   | Heisenberg, Werner     | science           |    197 | Penguin          |
|  21 | Making Software                                        | Oram, Andy             | computer_science  |    232 | O'Reilly         |
|  .  | .......                                                | .......                | ....              |    ... | ....             |
|  .  | .......                                                | .......                | ....              |    ... | ....             | The ChatSQL consists of two main parts. First of all, mysql queries are generated from the given plain text via ChatGPT. These generated queries are executed. In the second step, the results returned in the database are evaluated. At this stage, the results can either be presented directly to the user or sent back to ChatGPT for further analysis and interpretation. So you can chat about your database with ChatGPT. Suppose the user wants “Show me the book type fiction which they height bigger than 175 and smaller than 178. The author shouldn’t be ‘Doyle, Arthur Conan’.”. So the following command can be used in this case. python3 chatsql.py -p 'Show me the book type fiction which they height bigger than 175 and smaller than 178. The author shouldn't be 'Doyle, Arthur Conan'. ' As a result, the following information is obtained. CHATGPT QUERY------------------:
SELECT * FROM bt WHERE Genre = 'Fiction' AND Height > 175 AND Height < 178 AND Author != 'Doyle, Arthur Conan'
RAW RESULT------------------:
[(32, 'Pillars of the Earth, The', 'Follett, Ken', 'fiction', 176, 'Random House'), (37, 'Veteran, The', 'Forsyth, Frederick', 'fiction', 177, 'Transworld'), (38, 'False Impressions', 'Archer, Jeffery', 'fiction', 177, 'Pan'), (72, 'Prisoner of Birth, A', 'Archer, Jeffery', 'fiction', 176, 'Pan'), (87, 'City of Joy, The', 'Lapierre, Dominique', 'fiction', 177, 'vikas'), (128, 'Rosy is My Relative', 'Durrell, Gerald', 'fiction', 176, 'nan')]
PROCESSED RESULT------------------ :
The books 'Pillars of the Earth, The' by Ken Follett, 'Veteran, The' by Frederick Forsyth, 'False Impressions' by Jeffery Archer, 'Prisoner of Birth, A' by Jeffery Archer, 'City of Joy, The' by Dominique Lapierre, and 'Rosy is My Relative' by Gerald Durrell are all fiction books with 176 or 177 pages published by Random House, Transworld, Pan, Vikas, and Nan, respectively. If your database columns are named appropriately, chatgpt will understand these names and respond queries accordingly. However, there may be instances where the column names in the database are not meaningful or ChatGPT may not fully figure out their context. Hence, in order to ensure the system functions correctly, It is necessary to provide ChatGPT with prior information about the database. Info.json file can be used to adding information. +-----+--------------------------------------------------------+------------------------+-------------------+------+------------------+
| ID  | aa                                                     | bb                     | cc                | dd   | ee               |
+-----+--------------------------------------------------------+------------------------+-------------------+------+------------------+
|   1 | Fundamentals of Wavelets                               | Goswami, Jaideva       | signal_processing |  228 | Wiley            |
|   2 | Data Smart                                             | Foreman, John          | data_science      |  235 | Wiley            |
|   3 | God Created the Integers                               | Hawking, Stephen       | mathematics       |  197 | Penguin          |
|   4 | Superfreakonomics                                      | Dubner, Stephen        | economics         |  179 | HarperCollins    |
|   5 | Orientalism                                            | Said, Edward           | history           |  197 | Penguin          |
|  .  | .......                                                | .......                | ....              |    ... | ....           |
|  .  | .......                                                | .......                | ....              |    ... | ....           | As an example, let’s have a badly named database as below. In this case, the required information about the database is inputted into the info.json file. {“bt”: “Table Name”, “aa”: “Title of the book”, “bb”: “Author of the book”, “cc”: “Type of book”, “dd”: “Height of the book”, “ee”: “Book Publisher”} and then use the same command: python3 chatsql.py -p 'Show me the book type fiction which they height bigger than 175 and smaller than 178. The author shouldn't be 'Doyle, Arthur Conan'. ' Even if the column names in the database are poorly selected, chatgpt generates the correct query because we provide the correct information {'query': "SELECT aa, bb, cc, dd FROM bt WHERE cc = 'fiction' AND dd > 175 AND dd < 178 AND bb != 'Doyle, Arthur Conan'", 'raw_result': "[('Pillars of the Earth, The', 'Follett, Ken', 'fiction', 176), ('Veteran, The', 'Forsyth, Frederick', 'fiction', 177), ('False Impressions', 'Archer, Jeffery', 'fiction', 177), ('Prisoner of Birth, A', 'Archer, Jeffery', 'fiction', 176), ('City of Joy, The', 'Lapierre, Dominique', 'fiction', 177), ('Rosy is My Relative', 'Durrell, Gerald', 'fiction', 176)]", 'processed_result': '\nThe books "Pillars of the Earth, The" by Ken Follett, "Veteran, The" by Frederick Forsyth, "False Impressions" by Jeffery Archer, "Prisoner of Birth, A" by Jeffery Archer, "City of Joy, The" by Dominique Lapierre and "Rosy is My Relative" by Gerald Durrell are all fiction and have page lengths of 176 or 177.'} The next project could be on generating queries (mongo, sql) from prompts with free models (Llama). Project Repo : https://github.com/ademakdogan/ChatSQL Github : https://github.com/ademakdogan Linkedin : https://www.linkedin.com/in/adem-akdoğan-948334177/ References [1] Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P. and Amodei, D. (2020). Language models are few-shot learners. arXiv preprint arXiv:2005.14165. [2] Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI Blog. [3] Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N. and Polosukhin, I. (2017). Attention is all you need. In Advances in neural information processing systems (pp. 5998–6008). [4] Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Vol. 1, pp. 4171–4186). [5] Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., & Zettlemoyer, L. (2019). BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. arXiv preprint arXiv:1910.13461. [6] Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., … & Liu, P. J. (2019). Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv preprint arXiv:1910.10683. [7] Vaswani, A., & et al. (2017). Transformer-XL: Attentive language models beyond a fixed-length context. arXiv preprint arXiv:1901.02860.

ChatSQL: Enabling ChatGPT to Generate SQL Queries from Plain Text

চ্যাটএসকিউএল: প্লেইন টেক্সট থেকে এসকিউএল কোয়েরি তৈরি করতে ChatGPT সক্ষম করা

ChatSQL: ChatGPT aktivieren, um SQL-Abfragen aus reinem Text zu generieren

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ChatSQL – Activation de ChatGPT pour générer des requêtes SQL à partir de texte brut

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ChatSQL: ChatGPT를 활성화하여 일반 텍스트에서 SQL 쿼리 생성

ChatSQL : habilitando o ChatGPT para gerar consultas SQL a partir de texto simples

ChatSQL: ChatGPT'nin Düz Metinden SQL Sorguları Oluşturmasını Etkinleştirme

ChatSQL: Bật ChatGPT để tạo truy vấn SQL từ văn bản thuần túy

ChatSQL：启用 ChatGPT 从纯文本生成 SQL 查询

If what the AI fanatics and scaremongers predict comes true and generative AI takes away writing jobs, what will become of content writers like me? Today, I’m wearing my thinking cap and ready to imagine a dystopian world where I’m replaced by a machine. G , the new can deliver human-like content within seconds. And with just that ability, this fancy-schmancy technology has already revolutionized the content and marketing industry. enerative AI ‘Lord of the Content,’ It works faster and more efficiently than humans and has automated the entire content creation process, from researching and writing to editing and publishing, thus reducing the cost of human resources. With custom training data, generative AI can also produce virtually indistinguishable branded content from human-written one. What becomes of the common, average content writer now? All About the BOTS “To err is Human; To not err is BOT!” AI robots now churn out faster than you can say ‘artificial intelligence.’ clickbait headlines and fake news “A machine wins the Pulitzer.” This is what reality is now. All my dear content creators, there is no doubt that AI bots are coming for our jobs. Who will need humans when the bots can do everything, from writing to drawing and creating memes to producing research papers? At least they don’t spill coffee on the keyboard or accidentally reply-all to company emails. These AI bots don’t need tea breaks or vacations and don’t suffer from writer’s block or get distracted by cute cat videos. In fact, their lightning-fast processing power generates more content than we ever could and make us all look like slow, clumsy typewriters. (In such a case, we could create a support group for displaced writers or take up new hobbies, like finger painting or gardening. Either way, our days as creative geniuses behind content are already numbered!) *cue sad music* Human Writers, Is There a Ray of Hope? Well, as they say, there is a light at the end of the tunnel. Irrespective of generative AI’s advantages, relying too heavily on it has . consequences MAJOR consequences. AI-generated content lacks the touch of human creativity and originality. This has resulted in a across different industries and a loss of the unique voice and perspective that makes content engaging and memorable. homogenization of content It also lacks the humans can bring to content creation, which is crucial in marketing and storytelling. emotional intelligence And don’t even get me started on sarcasm. Can AI understand the subtle nuances of a sarcastic remark? Unfortunately, robots are notoriously bad at detecting irony, which means they’ll never be able to write content that makes you roll your eyes and mutter “Yeah, right” under your breath. Good News: This Is Not the End but a New Start. In a world dominated by AI, the content writing community needs to sit back and rethink the value they can bring to the table. And if they can’t find something solid, then they need to start creating it. Here is a list of alternate career options to consider in case bots eat up your job. Human writers can write specialized content requiring expertise and creativity, such as in-depth analysis, opinion pieces, and storytelling. AI cannot write how humans write regarding emotions, feelings, context, opinion, and other human-specific aspects based on their varied experiences. Human Intelligence (HI) Writers: Present and future worlds are full of generative AI written content. To make AI-generated content more exciting and relevant, brands must qualify them on HI criteria by having human editors on board. HI Editors: Human content writers can find opportunities where integration of both HI and AI is needed for a successful product or service. Companies can hire humans to add human-specific characteristics to their content. In this way, they can produce it fast and optimize it for human audiences. HI-AI Collaborators: Content writers can find their relevance in areas where specialized content based on human psychology and experiences is required. No AI bots can replace such jobs, ever. Human Content Specialists: Human writers can seek work in IT companies developing AI bots like OpenAI to provide human inputs/expertise to improve the quality of AI content writers. AI Content Skill Enhancers: Content writers can learn and gain expertise in AI writing tools, and then they can educate people on how to use AI writing bots optimally. They can even prepare user guides and become AI educators in universities. AI Optimal Utilization Coaches: If required, human writers can upskill and move into the roles such as analysts, project managers, program managers, AI software development, and big data analysts for the AI industry. Management Roles: Human content writers can provide valuable inputs in research contributions towards Natural Language Processing (NLP). NLP Researchers: Technology is ever-changing to meet the fast-changing needs of the modern world. So, there is always scope for improvement in any programmed tool. And when it comes to debugging, no one can do it better than a human writer. After all, these generative AI tools are made by humans for humans. AI Writing Tools Debuggers: As I imagine the dystopian world where content writers are replaced with their AI counterparts, I’m also imagining a positive, utopian world where content writers are not stuck creating boring, repetitive content. As Sabine Hauert, the Co-founder of , says, Robohub.org “Robots are not going to replace humans; they are going to make their jobs much more humane. Difficult, demeaning, demanding, dangerous, dull — these are the jobs robots will be taking.” To some content writers, the future may look bleak. But I believe if generative AI tools become the centric force in the content creation process, our jobs will only get more creative — where we’re valued for the ideas we bring to the table in shining words. And we’ll be better appreciated for it. Does that make you feel better, at least a little bit? Also published here

What Becomes of the Common Content Writer After AI Takes Over?

We were about an hour into the board meeting and one of the board members looked right at me and asked me a question— I tried my best to focus and say something, but the lights in the room were getting unmanageably bright. My head was hurting uncontrollably. I felt very nauseous, so I excused myself and ran to the bathroom. I tried my best to throw up, but the more I would try, the more my head would hurt. Eventually I gave up, told the board and my coworkers that I had to go home. About 4 weeks before that incident, I had been taking about 2–3 Excedrins . My headaches were getting persistent and uncontrollable and only Excedrin (that had caffeine it) would help. In fact my doctor had even given me advice on how frequently I should take Excedrin. He had also told me that to get the pain reliever into my bloodstream sooner, I should take the Excedrin with a carbonated drink. I did all of that. The Excedrin would give me moderate relief but as soon as it wore off, I felt even sicker than before. Vicious cycle. a day The day after the board meeting, I was back at work and once again had another uncontrollable headache. This time the nausea got the better of me. In fact I was having trouble keeping food or drink down. So my wife rushed me to the ER, where they gave me pain relievers intravenously. I remember the ER doctor telling me, “ ” I went back to my primary care doctor, who referred me to a . And the diagnosis was, . I had also learned the very hard way about . have you gotten checked for migraines? neurologist migraines the long term side effects of using NSAIDs like Excedrin My neurologist very quickly got me started on a drug called . The recommended dose was 100mg. As someone who has stayed away from prescription drugs all my life, I decided to start with 50mg. I was also given — a migraine abortive. I was told Sumatriptan was a “ripcord”, in that, if I felt a migraine coming on, I should immediately take some Sumatriptan (100mg). Sumatriptan was a magical drug. It made my mouth super dry, but it helped me get numb to the pain. Topamax or Topiramate Sumatriptan About 6 weeks of staying on Topamax, I started noticing some interesting patterns that I had been warned off. I would try to communicate but on occasion, words wouldn’t come out of my mouth. The thoughts were crystal in my head, but I couldn’t speak. Regular foods started tasting bland and weird. In fact, most times I felt like my appetite wasn’t there. Within 6 months of using Topamax regularly, I lost about 20lbs (went from 150lbs to about 130lbs). No matter what I tried, I couldn’t gain weight. When I told my neurologist about this, he joked, “ ” On my request, my neurologist also started researching alternatives to typical prescription medications. So I also started taking Butterbur, Riboflavin, Feverfew and CoQ10. All in all, the Topamax (50mg) + Sumatriptan (50mg) combo was working. I became the guy that had Sumatriptan in his backpack, by the bedside and some at work. My migraines were down from 8–10 a week to about 3–4 a week. But the 3–4 a week were seriously debilitating. people would kill to have that sort of weight loss. In fact, I knowlayers and bankers who take Topamax just to keep their weight down. For about 4 years, I stayed on this combo. My neurologist never suggested anything to entirely eliminate the migraines per se — in his experience of having done this for 30 years, no one had entirely gotten rid of their migraines. Our thesis, however, was that the migraines were triggered by lack of sleep. So in addition to the pill cocktail, my neurologist also suggested Magnesium, . My migraines were particularly bad on flights — I couldn’t get through a 5 hour flight without at least 150mg–200mg of Sumatriptan. Which means I also chugged water constantly because of the dry mouth. Which also means I had to constantly go to the bathroom. Middle seats were the bane of my existence. which is known to aid with sleep The one other nasty side effect — I was constantly “crabby”. I wasn’t quite myself. I recall being obsessed and quickly getting upset over mundane things. I tried to work out, but my head would start pounding as soon as I tried anything that was remotely exertive. I couldn’t run or walk long distances. As someone who had spent their entire life playing basketball, my life had become very sedentary. People would constantly tell me that I had lost weight, and it wasn’t like a “ ”, it was a “ ”. hey, you are looking good wow, you look creepily thin After about 4 years of seeing the same neurologist, I decided to get a second opinion. In July 2017, I made an appointment at the UCSF headache center. I met a , and he assessed me very briefly. He asked me about my coffee drinking patterns. The coffee snob that I was, I told him about the delicious light roasts I had to have morning. About 1 cup a day — that’s all. But it had to be at least 1 a day. I had been drinking coffee for about 15 years. Dr. Levin interrupted me and said, “ ” I told him that I had tried that before and I would get serious withdrawal headaches — so he suggested I wean off coffee gradually. I was dubious, I couldn’t function without coffee and there was just no way I wasn’t going to do it. Dr. Morris Levin every I’ve heard enough. Stop the coffee immediately. That’s it. You don’t even need to schedule a follow up appointment. Good luck. I had been a long time follower of and I finally got a chance to listen to . These words stuck with me: Shane Parrish and the Farnam Street Blog this podcast with Naval really We also unconsciously pick up habits in the background and we keep them for decades. We may not realize that they’re bad for us until we’re ready to move on them. … What we do is we accumulate all these habits. We put them in the bundle of identity, ego, ourselves, and then we get attached to that. … It’s really important to be able to uncondition yourself, to be able to take your habits apart and say, “Oh, okay, that’s a habit that I probably picked up from when I was a toddler and I was trying to get my parents attention. Now I’ve just reinforced it and reinforced it and reinforced it and I call it a part of my identity. Is it serving me anymore? Is it making me happier? Is it making me healthier? Is it making me accomplish whatever I want to set out to accomplish right now?” … I did a lot of habit changes over the last few years. I’ve now got a daily workout that I do, which is a great habit. I cut down heavily on drinking. It’s not totally eliminated, but it’s mostly gone. I dropped caffeine. … You can untrain yourself. It’s just hard. It takes work. It takes effort. Usually the big habit changes comes when there’s strong desire-motivators attached to them. After my daughter’s 4th birthday, I had decided to make a concerted effort to get healthier, both physically and mentally. With that commitment to myself and my family, with Dr. Levin’s suggestion, and Naval’s take on habits, I decided to, gradually but surely, quit coffee. At this point, I was still getting about 3–4 migraines a week, but as I started going off of coffee, I noticed my frequency of migraines was declining. I used to get withdrawal headaches, but those were very different from the migraines, and very manageable. It took about 6 weeks to get off of coffee entirely. Finally in mid-September, I noticed my migraines had all but stopped. I was entirely off of any form of caffeine at this point. And coincidentally just around then my Topamax prescription had run out. I decided not to refill it. It turns out I was addicted to my . It has now been . I hesitated to write this post for the longest time — not only am I superstitious, but I have been very concerned that the migraines would recur. I have since taken 4 cross country flights without any Sumatriptan in the last 3 months — no migraines. More importantly, my taste buds are back. . I have been working out consistently about 4–5x/week now, and I get no migraines when I work out. The most interesting thing however was how I felt like my “peripheral vision” had returned. We live on top of a hill, and every weekday we drive down the hill to go to work. A month or so ago, I noticed the most amazing view from this hill. When I mentioned the view to my wife, she said, “ ” I was just noticing it! When previously I felt like I was struggling for words, I am also now able to listen, comprehend and respond more cogently. migraine trigger about 3 months that I have been entirely migraine free I have since gained about 11lbs yeah, you know we do this drive everyday. Are you just noticing it? My weight gain since going off of Topamax (via ) HealthMate And an interesting byproduct of the exercise, my had increased by ~50%: HDL via Forward I have read about the . But to me coffee is a dangerous addiction. Had it not been for Dr. Levin and , I would not have thought to challenge my coffee addiction. Fairly often I meet fellow migraine sufferers and we share stories. When I tell them that coffee was the cause of my migraines, they are usually in disbelief. Most commonly I hear, “ ”. Does it though? amazing benefits of coffee Naval Ravikant but the coffee usually makes me feel better Migraines are debilitating and extremely painful. If you are a migraine sufferer, I am so so sorry. There is no known cure for migraines, and there isn’t a consistent pattern for what triggers migraines. Naval’s advice was extremely poignant for me — so if you are a migraine sufferer, it might not hurt for you to revisit your habits. It has definitely changed my life for the better. PS: Please consult with your doctor or neurologist before making any changes to your diet.

I was addicted to my migraine trigger

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