Anna Solovyova’s Post

I even cannot find the words to describe the level of madness that happens in this world when children under chemo therapy are sitting on the street waiting to be evacuated while a terrorist state bombing Kyiv today. We all think about innovation and progress but does it really make any sense when we as humanity are losing our last chance to be called Humans?

Women’s health gap equates to 75 million years of life lost due to poor health or early death each year. Closing the gap would give the 3.9 billion women in the world today an extra seven healthy days a year, or an average of 500 days over a lifetime. 6 conditions that highlight the gender health gap: 1. Heart diseases 2. Endometriosis 3. Autism 4. ADHD 5. Autoimmune conditions Each of these diseases caused not only economic problems and high costs for clinical care but also significantly affected the quality of the women's lives. The full article is here https://lnkd.in/dYvH-v3d

Suppose you are a VC, Early investor, or CIO trying to keep your eye on the industry trends. In that case, you’ve probably heard already about hallucinations, context shifts, and accuracy measurement problems in LLMs. These scary concepts kill motivation to invest in LLM-based projects and build RnD departments. Are they really so scary? Yes, but just for now, you have a good strategy to cope with them. Is this strategy already known? Yes, old but still one of the most effective approaches- knowledge graphs in combination with fresh new RAGs will allow you to keep your models free of hallucinations, stable in accuracy, and easily adaptable for context change. Btw, do you know that knowledge graphs are seeing as one of the most impactful AI enables during this year?🙌🏻 How big companies like Deutsche Telekom and Microsoft are seeing the future of LLMs adoption you can find here https://lnkd.in/d4B3t56z

Weareables in FemTech🌷 About 1.5 year ago Oura has arrived in my life and 1 year ago ave added Whoop to it. And yes, I have also Apple Watch but still I use more heavily Oura and Whoop. Why? Simple thing- they not only track woman health metrics but also provide deep insights. Simple to say but really hard to achieve from data perspective, so I’m really inspired by the technology these companies using🔥 Here you can find more insights about this topic btw https://lnkd.in/dC7BNhtc The wearables market is inundated with data, and the challenge is making this data actionable. Interdépendances between different events that affect the data is the missing peace to build a good predictive solutions. To achieve this partnering and cooperation with other FemTech products is the key to success. Amontg other, Oura and Whoop currently working together with Natural Cycles, Flo, and Gl. As wearables continue to win the market with more elegant solutions, the potential for them in FemTech is immense. Starting with the simple insights about wellbeing and emotions, I hope that in a few years we will see more solid simplifions aimed for personalised health management and early diagnosis of health related issues in FemTech🙌🏻 #FemTech #Wearables #HealthTech #WomenInTech #Innovation

Last week I enjoyed a great book “What I Talk About When I Talk About Running” from Haruki Murakami. Despite the naming that leaves the feeling of talking about the running experience, this book gave me a lot of thoughts on the business and life in general: 1. The Power of Routine: Murakami highlights the importance of discipline and routine. For him, the daily habit of running isn’t just about staying fit; it’s a cornerstone of his writing process. This consistency helps him build the stamina and focus he needs to craft his novels. 2. Finding Solitude: Running provides Murakami with precious moments of solitude. It’s during these runs that he finds clarity and space to reflect deeply, which in turn fuels his creativity. This quiet time alone is essential for his writing. 3. Embracing Endurance: Both long-distance running and writing require a great deal of endurance and perseverance. Murakami beautifully draws parallels between the two, showing how pushing through the tough miles or challenging chapters leads to a sense of accomplishment and growth. 4. Mind and Body Harmony: The book delves into the mind-body connection, underscoring how physical health influences mental well-being. For Murakami, staying physically active through running helps keep his mind sharp and his creative juices flowing. 5. Personal Fulfillment: Beyond professional achievements, running gives Murakami a deep sense of personal fulfillment. It’s a space where he sets his own goals and finds satisfaction purely for himself, separate from his identity as a writer. 6. Adapting with Age: Murakami also touches on the realities of aging, discussing how it affects both his running and writing. He candidly shares his experience of adapting to these changes, embracing a flexible approach and adjusting his goals with grace. It’s a Mohican feeling to find so many insights in just 170 pages ♥️ Read more, it makes you feel happiness 😉

Is Your Data Ready for GenAI? In the world of AI, the "garbage in, garbage out" principle means that bad data leads to bad results. Here’s a simple guide to help you understand the differences between data needed for classical machine learning (ML) and GenAI, and how to check if your data is up to the task. 1. Data Relevance Classical ML: Data should be specific to the task, like predicting sales based on past trends. GenAI: Data should be diverse and rich, enabling the AI to generate new content or insights. 2. Data Volume and Variety Classical ML: Often requires large amounts of structured data like spreadsheets. GenAI: Needs even more data, including unstructured types like text, images, and audio. 3. Data Quality and Integrity Classical ML: Requires clean, accurate data to ensure reliable predictions. GenAI: Also demands high-quality data but with even more emphasis on diversity and detail to create meaningful outputs. 4. Data Labeling and Annotation Classical ML: Labels are crucial for supervised learning, such as tagging emails as spam or not spam. GenAI: Precision in labeling is even more critical, especially for generating nuanced and contextually accurate content. 5. Data Privacy and Compliance Classical ML: Must comply with data regulations, particularly for personal data. GenAI: Requires stringent privacy measures due to the potential sensitivity of generated content and insights. 6. Data Access and Integration Classical ML: Data needs to be easily accessible for model training and validation. GenAI: Data integration should be seamless, allowing for real-time data flow and updates to enhance the AI's learning process. 7. Data Freshness Classical ML: Regular updates are needed to keep models relevant. GenAI: Continuous updates are crucial to maintain the relevance and creativity of generated content. With the right data, the possibilities of what your business can achieve with GenAI are limitless. But the cost for this data might be too high to invest in GenAI AI atm. Think critically before making this important strategical choice 🙌🏻

Startup life is a constant learning, especially when you launch your product and test it with early users🙌🏻 I’m exactly in this period now, so I decided to share more relevant resources and books that I find every month trying to crack the product market fit code and I hope that more people in my network will make a big step forward to develop new interesting products:) So this month, I would definitely recommend: 1. «Founding sales» Peter Kazanjy- this book is more about B2B sales but it gives a lot of very interesting concepts that with a bit of creative brain work can be implemented for B2C and B2B2C products 😎 and it contains tens of useful links in each paragraph 👌 2. «$100M leads» from Alex Hormozi was surprisingly cool and insightful for me 👍🏻 despite very populistic name this book gives a good overview of the percosal brand value, schemas of warm and cold outreaches and main hacks how to get people interested in trying your product 🔥 3. «How to get Users and Grow » https://lnkd.in/dvE9mx9Q lecture from Gustaf Alströmer 🇺🇦 - my top video in Y Combinator lectures serie 🙌🏻 1 hour of this lecture will save a lot of your time in the future, for sure👌 4. «Developing profitable strategies» https://lnkd.in/d2arYHDW lecture from MIT- classics that never gets old and that you need to watch at least once a year developing new products 🫶🏻 It was very interesting month, looking forward to all new interesting insights in June 🐇

During #mentalhealthweek I want to empasize a very simple rule to follow that will help you dramatically to improve your mental state: right now stop scrolling your feed here and pause dumb scrolling in any other social network👍🏻 Just concentrate on what you are doing and what you want to accomplish during this week (and not forget to say yourself how great you are to achieve all that you have)♥️ Social networks such as LinkedIn are great for connecting people and developing interesting ideas, so use it for this matter and not just to ghost other successes and blaming you for the absence of the long list of achievements 🫶🏻 You are great and you are doing the right things, just remember that!

You cannot build innovation in healthcare without understanding this simple truth. While the majority of the AI-based tools for health professionals are aimed at saving humanity, doctors would be much happier to have the tools that allow them to reduce organization noise and concentrate on the things that they are prepared for - diagnosis and treatment. Take a look on a very progressive AI startups aimed to build another one diagnosis tool for images, text files, etc. They have fascinating teams and technology behind them but they struggle to find user acceptance and develop a company from the product. Why? They aimed the area against the interest of their users- doctors. In contrast, handy tools that have proven track of reducing paperwork and organizational workload in clinics are easily adapted and find their PMF writhing first year. Let us adapt innovation in healthcare where it’s needed and not where its fancy, that’s they way to make medicine better and more efficient 🔥