Ivee

ivee

Hi everyone, I am really excited to present some of the insights and strategies that shaped my journey in digital tech business development, AI, and global market expansion. A Bit About My Background 📝 With 14+ years of international experience in the United States, Europe, China, and Southeast Asia, I have operated in nearly all walks of businesses. The work has taken me from building AI and ML solutions for Yandex and Toloka to running international sales for large enterprises, and even launching subscription services for millions of users across Asia. I want to share some strategies and lessons learned in this post, hoping to help you navigate this complex world of business development, lead generation, and AI-driven growth. How to Build a Sales Engine Without a Massive SDR 🏆 Building global door-opener teams doesn't always have to mean pounding the pavement with dozens of SDRs. I have built completely new international business operations for 7 companies. One of the most impressive was for pro-glance.com, an expansion from zero to exporting into 35 countries within six months. This is how we did it: Data-driven targeting: By focusing on perfectly accurate Ideal Customer Profiles, we could focus our efforts where they would reap the most value.
Negotiation Mastery: I learned how to manage a deal from multiple continents, where cultural nuances and negotiation tactics really made a difference in closing key partnerships.
**Resource Efficiency:**We focused on building a system that maximized impact with minimal resources, instead of building a huge sales force. Unorthodox partnerships can magic your business overnight—and they are usually the last things you expect. While working at RPC LLC, I was leading sales for the company in international markets since the pandemic. We closed multiple deals, each above $100,000, with Chinese partners, and all that with a shoestring marketing budget due to the closed borders of these countries. Key takeaways: 💥 Cultural Competence: My fluency in Mandarin was used to leverage trust and relationships beyond belief.
With a meagre marketing budget of $1,000, we were able to win hearts and get our job done excellently. This was possible due very specific and niche outreach in Chinese social media and also through accurate lines of networking. Think first, where your leads might be, what do they use, and what they read, so you can get in front and catch them. Despite all, cold calling doesn’t work, you need to engage smartly, and find those who really might be your customers starting from SEO and social media content up to search engine ads.

Long-Term Relationships: Partnerships do not mean a short-term gain. It is the relationships that helped us to secure continuous growth even in the most adverse of situations. Build trust with your potential partner, even if he doesn’t show interest in your product right now, he might help you with networking or other means. From Content Moderation to AI-Driven Success 🏦 🎰 The rise of AI has been a game-changer. At Yandex Toloka, I led efforts from development to launch in creating AI/ML solutions that are being used in a wide variety of mission-high scenarios, from content moderation to fraud detection. Here are a few highlights: Search Optimization for E-commerce Giants: Develop and implement search relevance models for big e-commerce players, from Zalora to Tokopedia, in a way that would optimize their search engines, making them better for customers and increasing the conversion rate. Content Moderation at Scale: Development of an AI content moderation system attuned to vast amounts of text, video, and image content produced daily across multiple languages and regions in Southeast Asia.


Advanced AI Applications: Projects in this portfolio include checking weather conditions using IBM Watson to developing a stock market fraud detection model. They show the adaptability and strength of Artificial Intelligence in solving a wide range of complex problems. Whether you are trying to leverage AI in your business for success or developing a B2B SaaS in generative AI, I have designed and outlined frameworks and methodologies that take you through the process seamlessly. When you’re trying to acquire leads within AI market, everything becomes more complex and you should be super sharp with your outreach. Types of lead generation and methods: 💥 Firstly, you should understand there 2 types of lead generation: inbound and outbound. Inbound is when you use GoogleAds or SEO to acquire warm leads that already showed some interest to your topic or even to your solution personally. Outbound is when you try to outreach through cold calling, LinkedIn messaging and emails cold leads that most probably didn’t show any interest or have little interest to what you’re doing/selling/promoting. For B2B SaaS products you should have both (inbound and outbound) and it might take time to set up efficiently the sales pipeline and marketing engine, but efficiency and accuracy are the keys to the door that will boost your sales. You will have to experiment in variety of ways and methods. One of the tools that helped me and which is crucial for both outbound and inbound lead generation is Zoominfo, and particularly “Buyer Intent” feature that shows you which leads showed interest to your topic and potentially your product. You can check for alternatives - Seamless.ai, Telescope App etc. Secondly, never forget to create target lists of companies and ICP profiles, this could help not only you, but other team members to identify which companies are crucial for you to get to and they will help you acquiring leads from them. Thirdly, for cold lead generation you should post a lot and use influence marketing. Think of tools like Ivee, Lempod, chatGPT and others that might help you launch your B2B influence marketing and generate leads as well. Building a B2B Empathetic AI Business 🪄 Currently, I'm building a B2B empathetic artificial intelligence business at Ex-human that would fundamentally change how humans interact with machines. Our goal is to create naturally human-like, empathetic, multimodal conversations long before any tool can be built, such as ChatGPT or DALL-E. This is what we are doing now: Next-gen GTM Strategies: Launching new technologies in competitive markets needs a savvy go-to-market strategy. Leading with this approach, we fuse both inbound and outbound lead generation with digital performance marketing to pave the road to success.


Cross-Industry Applications: Our AI technology is versatile, as shall be the applications in a broad range: in-game NPCs to dating sites, smart gadgets, and AR/VR environments. I am quite excited to share more with you as we continue to build and refine our strategies. To Close I hope these insights shared valuable strategies and perspectives that you can replicate in your own ventures. I for sure have had my own journey full of lessons learned across industries and markets; I am always open to sharing more. Do not hesitate to contact me in case of any questions or thoughts. Let's grow and learn together! Hi everyone, I am really excited to present some of the insights and strategies that shaped my journey in digital tech business development, AI, and global market expansion. A Bit About My Background 📝 A Bit About My Background With 14+ years of international experience in the United States, Europe, China, and Southeast Asia, I have operated in nearly all walks of businesses. The work has taken me from building AI and ML solutions for Yandex and Toloka to running international sales for large enterprises, and even launching subscription services for millions of users across Asia. I want to share some strategies and lessons learned in this post, hoping to help you navigate this complex world of business development, lead generation, and AI-driven growth. How to Build a Sales Engine Without a Massive SDR 🏆 How to Build a Sales Engine Without a Massive SDR Building global door-opener teams doesn't always have to mean pounding the pavement with dozens of SDRs. I have built completely new international business operations for 7 companies. One of the most impressive was for pro-glance.com, an expansion from zero to exporting into 35 countries within six months. This is how we did it: Data-driven targeting: By focusing on perfectly accurate Ideal Customer Profiles, we could focus our efforts where they would reap the most value. Negotiation Mastery: I learned how to manage a deal from multiple continents, where cultural nuances and negotiation tactics really made a difference in closing key partnerships. **Resource Efficiency:**We focused on building a system that maximized impact with minimal resources, instead of building a huge sales force. Data-driven targeting: By focusing on perfectly accurate Ideal Customer Profiles, we could focus our efforts where they would reap the most value. Data-driven targeting: Negotiation Mastery: I learned how to manage a deal from multiple continents, where cultural nuances and negotiation tactics really made a difference in closing key partnerships. Negotiation Mastery: **Resource Efficiency:**We focused on building a system that maximized impact with minimal resources, instead of building a huge sales force. Unorthodox partnerships can magic your business overnight—and they are usually the last things you expect. While working at RPC LLC, I was leading sales for the company in international markets since the pandemic. We closed multiple deals, each above $100,000, with Chinese partners, and all that with a shoestring marketing budget due to the closed borders of these countries. Key takeaways: 💥 Key takeaways: 💥 Cultural Competence: My fluency in Mandarin was used to leverage trust and relationships beyond belief.
With a meagre marketing budget of $1,000, we were able to win hearts and get our job done excellently. This was possible due very specific and niche outreach in Chinese social media and also through accurate lines of networking. Think first, where your leads might be, what do they use, and what they read, so you can get in front and catch them. Despite all, cold calling doesn’t work, you need to engage smartly, and find those who really might be your customers starting from SEO and social media content up to search engine ads. Long-Term Relationships: Partnerships do not mean a short-term gain. It is the relationships that helped us to secure continuous growth even in the most adverse of situations. Build trust with your potential partner, even if he doesn’t show interest in your product right now, he might help you with networking or other means. Cultural Competence: My fluency in Mandarin was used to leverage trust and relationships beyond belief. With a meagre marketing budget of $1,000, we were able to win hearts and get our job done excellently. This was possible due very specific and niche outreach in Chinese social media and also through accurate lines of networking. Think first, where your leads might be, what do they use, and what they read, so you can get in front and catch them. Despite all, cold calling doesn’t work, you need to engage smartly, and find those who really might be your customers starting from SEO and social media content up to search engine ads. Cultural Competence: My fluency in Mandarin was used to leverage trust and relationships beyond belief. Cultural Competence: With a meagre marketing budget of $1,000, we were able to win hearts and get our job done excellently. This was possible due very specific and niche outreach in Chinese social media and also through accurate lines of networking. Think first, where your leads might be, what do they use, and what they read, so you can get in front and catch them. Despite all, cold calling doesn’t work, you need to engage smartly, and find those who really might be your customers starting from SEO and social media content up to search engine ads. Long-Term Relationships: Partnerships do not mean a short-term gain. It is the relationships that helped us to secure continuous growth even in the most adverse of situations. Build trust with your potential partner, even if he doesn’t show interest in your product right now, he might help you with networking or other means. Long-Term Relationships: Partnerships do not mean a short-term gain. It is the relationships that helped us to secure continuous growth even in the most adverse of situations. Build trust with your potential partner, even if he doesn’t show interest in your product right now, he might help you with networking or other means. Long-Term Relationships: From Content Moderation to AI-Driven Success 🏦 🎰 From Content Moderation to AI-Driven Success The rise of AI has been a game-changer. At Yandex Toloka, I led efforts from development to launch in creating AI/ML solutions that are being used in a wide variety of mission-high scenarios, from content moderation to fraud detection. Here are a few highlights: Here are a few highlights: Search Optimization for E-commerce Giants: Develop and implement search relevance models for big e-commerce players, from Zalora to Tokopedia, in a way that would optimize their search engines, making them better for customers and increasing the conversion rate. Content Moderation at Scale: Development of an AI content moderation system attuned to vast amounts of text, video, and image content produced daily across multiple languages and regions in Southeast Asia. Advanced AI Applications: Projects in this portfolio include checking weather conditions using IBM Watson to developing a stock market fraud detection model. They show the adaptability and strength of Artificial Intelligence in solving a wide range of complex problems. Search Optimization for E-commerce Giants: Develop and implement search relevance models for big e-commerce players, from Zalora to Tokopedia, in a way that would optimize their search engines, making them better for customers and increasing the conversion rate. Content Moderation at Scale: Development of an AI content moderation system attuned to vast amounts of text, video, and image content produced daily across multiple languages and regions in Southeast Asia. Search Optimization for E-commerce Giants: Develop and implement search relevance models for big e-commerce players, from Zalora to Tokopedia, in a way that would optimize their search engines, making them better for customers and increasing the conversion rate. Content Moderation at Scale: Development of an AI content moderation system attuned to vast amounts of text, video, and image content produced daily across multiple languages and regions in Southeast Asia. Search Optimization for E-commerce Giants: Advanced AI Applications: Projects in this portfolio include checking weather conditions using IBM Watson to developing a stock market fraud detection model. They show the adaptability and strength of Artificial Intelligence in solving a wide range of complex problems. Advanced AI Applications: Projects in this portfolio include checking weather conditions using IBM Watson to developing a stock market fraud detection model. They show the adaptability and strength of Artificial Intelligence in solving a wide range of complex problems. Advanced AI Applications: Whether you are trying to leverage AI in your business for success or developing a B2B SaaS in generative AI, I have designed and outlined frameworks and methodologies that take you through the process seamlessly. When you’re trying to acquire leads within AI market, everything becomes more complex and you should be super sharp with your outreach. Types of lead generation and methods: 💥 Types of lead generation and methods: Firstly, you should understand there 2 types of lead generation: inbound and outbound. Inbound is when you use GoogleAds or SEO to acquire warm leads that already showed some interest to your topic or even to your solution personally. Outbound is when you try to outreach through cold calling, LinkedIn messaging and emails cold leads that most probably didn’t show any interest or have little interest to what you’re doing/selling/promoting. For B2B SaaS products you should have both (inbound and outbound) and it might take time to set up efficiently the sales pipeline and marketing engine, but efficiency and accuracy are the keys to the door that will boost your sales. You will have to experiment in variety of ways and methods. One of the tools that helped me and which is crucial for both outbound and inbound lead generation is Zoominfo, and particularly “Buyer Intent” feature that shows you which leads showed interest to your topic and potentially your product. You can check for alternatives - Seamless.ai, Telescope App etc. Secondly, never forget to create target lists of companies and ICP profiles, this could help not only you, but other team members to identify which companies are crucial for you to get to and they will help you acquiring leads from them. Thirdly, for cold lead generation you should post a lot and use influence marketing. Think of tools like Ivee, Lempod, chatGPT and others that might help you launch your B2B influence marketing and generate leads as well. Building a B2B Empathetic AI Business 🪄 Building a B2B Empathetic AI Business Currently, I'm building a B2B empathetic artificial intelligence business at Ex-human that would fundamentally change how humans interact with machines. Our goal is to create naturally human-like, empathetic, multimodal conversations long before any tool can be built, such as ChatGPT or DALL-E. This is what we are doing now: This is what we are doing now: Next-gen GTM Strategies: Launching new technologies in competitive markets needs a savvy go-to-market strategy. Leading with this approach, we fuse both inbound and outbound lead generation with digital performance marketing to pave the road to success. Cross-Industry Applications: Our AI technology is versatile, as shall be the applications in a broad range: in-game NPCs to dating sites, smart gadgets, and AR/VR environments. Next-gen GTM Strategies: Launching new technologies in competitive markets needs a savvy go-to-market strategy. Leading with this approach, we fuse both inbound and outbound lead generation with digital performance marketing to pave the road to success. Next-gen GTM Strategies : Launching new technologies in competitive markets needs a savvy go-to-market strategy. Leading with this approach, we fuse both inbound and outbound lead generation with digital performance marketing to pave the road to success. Next-gen GTM Strategies Cross-Industry Applications: Our AI technology is versatile, as shall be the applications in a broad range: in-game NPCs to dating sites, smart gadgets, and AR/VR environments. Cross-Industry Applications : Our AI technology is versatile, as shall be the applications in a broad range: in-game NPCs to dating sites, smart gadgets, and AR/VR environments. Cross-Industry Applications I am quite excited to share more with you as we continue to build and refine our strategies. To Close To Close I hope these insights shared valuable strategies and perspectives that you can replicate in your own ventures. I for sure have had my own journey full of lessons learned across industries and markets; I am always open to sharing more. Do not hesitate to contact me in case of any questions or thoughts. Let's grow and learn together!

Scaling Digital Tech Businesses & AI Solutions: Lessons Learned Across Continents

Hey everyone! I’m Nataraj, and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus 100 days of AI was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon here or my personal website here. In today’s article, we’ll be looking to build a Semantic Kernel with the help of GPT-4. There is a lot happening in generative AI space. So much so that Nvidia the arms dealer of generative AI with its H100 chips is now surpassed Amazon’s market valuations. It is also a very dynamic space with lots of activity from startups and the big tech companies. In this post I will highlight three big trends that we might see in the next 12-18 months. 1 – Data Deals For last two decades we kept saying data is the new oil. This phrase will have real implications this year. A lot of companies have accumulated unique sets of data and have found a real product market fit. Recently a news broke out the Reddit made a deal to access to its data to an unnamed company for $60M. The terms of the deal are unknown but that’s $60M new revenue for Reddit. Look out for more deals from companies that have unique sets of data. 2 – Focus on Open Source Models Since Open AI launched chat gpt, the conversation was dominated by gpt series base models which are closed models, meaning no one except the Open AI team knows the details of how the model was trained, what data it was trained on & the parameters of the model. We will see more Open Source models take stage and capture attention. The main player in this arena to look out is Meta (Facebook). Meta is taking the page out of Google’s approach in mobile. While Apple’s mobile operating system was closed, Google strategy was to be an open source mobile operating system that fuels 80%+ of world’s mobile phones. So keep an eye out on Meta. 3 – Small Language Models Open AI proved to the world what is the power of Large Language Models (LLMs). But as every company in AI is racing to build product ready products and features and trying get enterprises adopt AI for their business. LLMs might not always be the best solution. A smaller model which can take less compute to train and uses less but more quality data might actually be better. These models referred to as SLMs could be run on mobile phones which will increase the access of AI to wider audience. Some of the SLMs to check out are: Phi by Microsoft
Orca by Microsoft
T5 by Google One of the main forcing function to adapt and innovate with SMLs is to reduce the compute cost and there by making AI more accessible. 4 – Focus on LLM Security I am not talking about data security to train the LLM. I am referring to instances where users can hack LLMs to do something that they are not supposed to or break just them. There are a lot of security issues that are cropping up on how to hack LLM behaviors. Some include: Jailbreak to make LLM answer something that it shouldn’t like making a banned substance at home.
Prompt Injection to hide prompt instructions that break LLMs
Data poisoning is embedding bad data on the internet which will be used by LLMs and can later be misused. There are more and more ways we are currently discovering that LLMs can be compromised as we fix the ones we know about. This will be one of the active areas where progress will be made in 2024 both on research & product side. 5 – Regulatory Implications It pretty clear that AI is going to have huge implications on the society across all sectors. It will cross paths with every aspect of society and as we have seen every big company announce major AI initiatives and investments into AI during 2022-23. Microsoft invested in Open AI & Inflection
Google & Amazon invested in Anthropic
Jeff Bezos invested in Perplexity
Airbnb acquired a stealth AI company called gameplanner.ai Regulators were already focused on big tech which blocked them doing any acquisitions in last 3 years. With this in the background we will see regulators both in the U.S and E.U closely watch Ai investments and also potentially detangle some of the investments. The investments were made primarily to avoid acquisitions because people who are running big tech companies know that it is going to be an uphill battle to get them approved. But even some of these investments might also come under scrutiny. That’s it for Day 14 of 100 Days of AI. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, subscribe to it. Follow me on Twitter, LinkedIn or HackerNoon for latest updates on 100 days of AI. If you are in tech you might be interested in joining my community of tech professionals here. Hey everyone! I’m Nataraj, and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus 100 days of AI was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon here or my personal website here. In today’s article, we’ll be looking to build a Semantic Kernel with the help of GPT-4. Hey everyone! I’m Nataraj, and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus 100 days of AI was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon here or my personal website here. In today’s article, we’ll be looking to build a Semantic Kernel with the help of GPT-4. Hey everyone! I’m Nataraj, and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus 100 days of AI was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon here or my personal website here . In today’s article, we’ll be looking to build a Semantic Kernel with the help of GPT-4. I’m Nataraj , I’m Nataraj 100 days of AI 100 days of AI here here here here There is a lot happening in generative AI space. So much so that Nvidia the arms dealer of generative AI with its H100 chips is now surpassed Amazon’s market valuations. It is also a very dynamic space with lots of activity from startups and the big tech companies. In this post I will highlight three big trends that we might see in the next 12-18 months. 1 – Data Deals For last two decades we kept saying data is the new oil . This phrase will have real implications this year. A lot of companies have accumulated unique sets of data and have found a real product market fit. Recently a news broke out the Reddit made a deal to access to its data to an unnamed company for $60M. The terms of the deal are unknown but that’s $60M new revenue for Reddit. Look out for more deals from companies that have unique sets of data. data is the new oil 2 – Focus on Open Source Models 2 – Focus on Open Source Models Since Open AI launched chat gpt, the conversation was dominated by gpt series base models which are closed models, meaning no one except the Open AI team knows the details of how the model was trained, what data it was trained on & the parameters of the model. We will see more Open Source models take stage and capture attention. The main player in this arena to look out is Meta (Facebook). Meta is taking the page out of Google’s approach in mobile. While Apple’s mobile operating system was closed, Google strategy was to be an open source mobile operating system that fuels 80%+ of world’s mobile phones. So keep an eye out on Meta. 3 – Small Language Models Open AI proved to the world what is the power of Large Language Models (LLMs). But as every company in AI is racing to build product ready products and features and trying get enterprises adopt AI for their business. LLMs might not always be the best solution. A smaller model which can take less compute to train and uses less but more quality data might actually be better. These models referred to as SLMs could be run on mobile phones which will increase the access of AI to wider audience. Some of the SLMs to check out are: Phi by Microsoft Orca by Microsoft T5 by Google Phi by Microsoft Phi by Microsoft Orca by Microsoft Orca by Microsoft T5 by Google T5 by Google One of the main forcing function to adapt and innovate with SMLs is to reduce the compute cost and there by making AI more accessible. 4 – Focus on LLM Security I am not talking about data security to train the LLM. I am referring to instances where users can hack LLMs to do something that they are not supposed to or break just them. There are a lot of security issues that are cropping up on how to hack LLM behaviors. Some include: Jailbreak to make LLM answer something that it shouldn’t like making a banned substance at home. Prompt Injection to hide prompt instructions that break LLMs Data poisoning is embedding bad data on the internet which will be used by LLMs and can later be misused. Jailbreak to make LLM answer something that it shouldn’t like making a banned substance at home. Jailbreak Prompt Injection to hide prompt instructions that break LLMs Prompt Injection Data poisoning is embedding bad data on the internet which will be used by LLMs and can later be misused. Data poisoning There are more and more ways we are currently discovering that LLMs can be compromised as we fix the ones we know about. This will be one of the active areas where progress will be made in 2024 both on research & product side. 5 – Regulatory Implications It pretty clear that AI is going to have huge implications on the society across all sectors. It will cross paths with every aspect of society and as we have seen every big company announce major AI initiatives and investments into AI during 2022-23. Microsoft invested in Open AI & Inflection Google & Amazon invested in Anthropic Jeff Bezos invested in Perplexity Airbnb acquired a stealth AI company called gameplanner.ai Microsoft invested in Open AI & Inflection Google & Amazon invested in Anthropic Jeff Bezos invested in Perplexity Airbnb acquired a stealth AI company called gameplanner.ai Regulators were already focused on big tech which blocked them doing any acquisitions in last 3 years. With this in the background we will see regulators both in the U.S and E.U closely watch Ai investments and also potentially detangle some of the investments. The investments were made primarily to avoid acquisitions because people who are running big tech companies know that it is going to be an uphill battle to get them approved. But even some of these investments might also come under scrutiny. That’s it for Day 14 of 100 Days of AI. That’s it for Day 14 of 100 Days of AI. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, subscribe to it. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, subscribe to it . subscribe to it Follow me on Twitter , LinkedIn or HackerNoon for latest updates on 100 days of AI. If you are in tech you might be interested in joining my community of tech professionals here . Twitter Twitter LinkedIn LinkedIn HackerNoon HackerNoon here here

100 Days of AI, Day 14: The Five Generative AI Trends to Watch Out for in 2024

AI-এর 100 দিন, দিন 14: 2024 সালে লক্ষ্য রাখার জন্য পাঁচটি জেনারেটিভ AI প্রবণতা

100 Tage KI, Tag 14: Die fünf generativen KI-Trends, auf die Sie im Jahr 2024 achten sollten

100 días de IA, día 14: Las cinco tendencias de IA generativa a tener en cuenta en 2024

100 jours d'IA, jour 14 : les cinq tendances de l'IA générative à surveiller en 2024

एआई के 100 दिन, दिन 14: 2024 में ध्यान देने योग्य पांच जनरेटिव एआई रुझान

AI の 100 日、14 日目: 2024 年に注目すべき 5 つの生成 AI トレンド

AI 100일, 14일차: 2024년에 주목해야 할 5가지 생성 AI 트렌드

100 dias de IA, dia 14: As cinco tendências de IA generativa a serem observadas em 2024

100 дней ИИ, день 14: пять тенденций генеративного ИИ, на которые следует обратить внимание в 2024 году

100 Gün Yapay Zeka, 14. Gün: 2024'te Dikkat Edilmesi Gereken Beş Üretken Yapay Zeka Trendi

100 ngày của AI, Ngày 14: Năm xu hướng AI sáng tạo cần chú ý vào năm 2024

人工智能 100 天，第 14 天：2024 年值得关注的五种生成式人工智能趋势

Beginning with the most important skill of the 21st century Everyone is very busy these days. There is just so much going on with our personal and professional lives. On top of it, lo and behold, something like artificial intelligence starts to gather steam and you learn that your skillset is getting terribly outdated over next two years. , I woke up to this rude awakening. It looked like was missing out on something very unique. When I shutdown my startup Zeading The relevance of a full stack developer will not be enough in the changing scenario of things. In the next two years, full stack will not be full stack without AI skills. It was time to take action. And I did what I thought was the only course of action to take now — to update my skills as a developer, my mindset as a product guy and my philosophy as an entrepreneur to become data oriented. As , renowned venture capitalist and thought leader in AI and Fintech so eloquently said to me, Spiros Margaris If startups and companies rely only on cutting-edge AI and machine learning algorithms to compete — it will be not enough. AI will be not a competitive advantage but a requirement. Do you hear anyone saying they use electricity as a competitive edge? Building my first neural network Photo by — Unsplash The common advice was to sign up for . It is a great place to begin but I found it hard to stay awake for long. Not to say that the course was bad or anything, but I really suck at staying attentive in lectures. My mode of has always been by doing, so I thought why the hell not, let’s implement our own neural network. Andrew Ng’s course on Coursera learning I did not jump straight to neural nets because it is some better way to learn. I was trying to familiarize myself with all the words in the domain so I can learn to speak the language. The first assignment is not to learn. But to familiarize. Coming from a pure Javascript and Nodejs background, I didn’t want to switch stacks just yet. So I searched for a simple neural net module called nn and used it to implement an gate with a dummy input. , I chose the problem that for any three inputs X,Y and Z the output should by X Y. AND Inspired by this tutorial AND var nn = require('nn')var opts = {layers: [ 4 ],iterations: 300000,errorThresh: 0.0000005,activation: 'logistic',learningRate: 0.4,momentum: 0.5,log: 100}var net = nn(opts) net.train([{ input: [ 0,0,1 ], output: [ 0 ] },{ input: [ 0,1,1 ], output: [ 0 ] },{ input: [ 1,0,1 ], output: [ 0 ] },{ input: [ 0,1,0 ], output: [ 0 ] },{ input: [ 1,0,0 ], output: [ 0 ] },{ input: [ 1,1,1 ], output: [ 1 ] },{ input: [ 0,0,0 ], output: [ 0 ] }]) // send it a new input to see its trained outputvar output = net.send([ 1,1,0])console.log(output); //0.9971279763719718 Such happiness! In my personal opinion, this was the most confidence building step that I had taken. When the output flashed as 0.9971, I realized that the network learned how to do an operation and ignore the additional input on its own. AND This is mostly the gist of machine learning. You give a computer program a set of data and it adjusts its internal parameters in such a way that it gains the ability to answer questions on new data with a decreasing error from what it observed from original data. This method, as I would later come to know, is also known as gradient descent. Photo by — Sebastian Raschka Priming my mind for artificial intelligence Photo courtesy — Unsplash O . nce I was brimming with confidence after I had made my first artificial intelligence program, I wanted to know what more I can do with machine learning as a developer I solved a couple of such as and . supervised learning problems regression classification I used a very limited data set to try to predict which team will win a given IPL match using (The predictions were really off, but it was kind of cool) multivariate linear regression . I played along with the to see what all things AI can do today (well enough that Google was doing it as a SaaS product) demos on Google Machine Learning cloud I stumbled upon , the esteemed venture fund. Truly one of the most handy resources for developers and entrepreneurs. AI Playbook , an awesome resource organized by Andreessen-Horowitz I started watching that is centered around Deep Learning and Machine Learning. Siraj Rawal’s awesome channel on Youtube I read this about how the showrunners at Silicon Valley built the . This was one of the most approachable examples of deep learning that we can do. awesome Hacker Noon post Not Hotdog app I read . Even though I couldn’t understand anything at much and it gave me a headache, I found out that after trying for some more time the concepts do actually begin to make sense. Andrej Karpathy’s blogs , who is Director of AI at Tesla With some courage, I started to implement (copy and paste) and tried to train the model and run the code on my local machine. Most times, it sucked because of the high training time most models take and I didn’t have a GPU. some of the deep learning tutorials verbatim Gradually, I switched my from Javascript to Python, and installed . tools Tensorflow on my windows machine This whole process was centred around passively consuming contents and building references in your mind so I can use later when I get a real consumer problem to work on. As Steve Jobs said, you can only connect the dots looking backward. Catching the chatbot train Photo by — Unsplash Being a major fan of the movie , I wanted to build chatbots. I took up the challenge and managed to build one using Tensorflow in less than two hours. I outlined this journey and the business needs of it in a few days back. Her one of my articles Fortunately, the article got really went viral and was featured in , , and . It was a great moment for me, personally, because I’ve just begun with tech blogging. But I think that this article was one of the landmark moments in my AI learning journey. TechInAsia CodeMentor KDNuggets It got me to make many friends on Twitter and LinkedIn, with whom I can discuss AI development at length and depth and can even reach out should I get stuck. I got a few offers to do consulting projects and the best part of all, young developers and AI beginners started to ask me how I began with AI. Which brings us to why I’ve written this article. To help more people take cues from my own journey and start their own. Starting is one of the most challenging parts of any journey. Salt and pepper Photo by — Unsplash It was definitely not easy. When I started getting stuck with Javascript, I jumped to Python almost overnight and picked up how to code in that. I started to get irritated when my models won’t train on my i7 machine or when even after hours of training, they would return gibberish results like a 50–50 probability of a team winning a Cricket match. Learning AI is not like learning a web framework. It is a skill that requires awareness of what is going on at the microscopic level of calculations and find what is more responsible for your output — your code or your data. AI is also not just one subject. It is an umbrella term used for anything from simple regression problems to killer robots that are going to kill us someday. Like every other discipline you get into, you might want to cherry pick the kinds of things in AI you want to be really good at like computer vision or natural language processing, or God forbid, world domination. In a conversation with from Atlantis Capital, a reputed industry leader in AI, Fintech, and Crypto, he confided to me that: Gaurav Sharma In the age of artificial intelligence, “being smart” will mean something completely different. We need people to perform the higher-order critical, creative, and thinking and the jobs that require high emotional engagement. You have to be fascinated by how computers suddenly how to do things on their own. Patience and wonder are the two key principles that you should cling. learn This is a big, big journey. Very tiring, very irritating and exceptionally time consuming. But the good part is, like every other journey in the world, this one also starts with a single step. Thanks for reading :) If you enjoyed it, hit that clap button below as many times as possible! It would mean a lot to me and encourage me to write more stories like this Let’s also connect on Twitter , LinkedIn , email or at my blog shivalgupta.com

How I started with learning AI in the last 2 months

It will come as no surprise to those of you reading this (thanks!), that the interest and applications of ‘ ’ is growing rapidly. Amazon Alexa and there is talk around for the next 10,000. I won’t be diving into specifics and discussing issues like . That is not what this post is about. Voice-Assistants recently hit 10,000 skills what will drive adoption retention There are lots of resources & tools, tons of cool products, frameworks, articles and people out there to help you learn about the landscape. 💫 Here are some that I find particularly useful 💫 This post is also on GitHub and open for suggestions, just submit a pull request by VoiceLabs The 2017 Voice Report 🤔 How To Use This : There is very little on the front focusing on Voice-Assistants. does the best one IMO. 📰 News newsletter Matt Hartman ( I’m thinking of starting one too —if you’re interested, sign up below!) : Always interesting to see the companies operating in these spaces. They are broken down into different categories so you can easily jump into ‘Building’, ‘Products’, ‘Analytics’ etc. If you think there are some that need adding, 🍜 Startups tell me here . This is just to outline some companies/funds that are very focused in the space right now. Again, if I’ve missed some worthwhile, 🤑 Funding: tell me here . These are some of the awesome people I follow and have come across. I’ve linked them all, you should check them out. If I’ve missed some worthwhile, you know to 👥 People & Posts: tell me here . Enjoy 😊! 🚀 I’ve launched something: Skills.wtf — A site to find the best Alexa Skills 🚀Also, I’ve added a little note about at the end of this post. A community helping facilitate connections to; an experiment I’m working on - Get a skill made/make skills for people/companies- Find investors active in the field- Intros to other active enthusiasts- Bounce ideas around with others- Advice & mentorship from experienced individuals- Resources and tools to help you build- Discover interesting products and companies 📰 News 🗞 Newsletters _Hearing Voices - This week's news about voice computing apps, delivered directly to your inbox. ..._www.getrevue.co Hearing Voices - Revue The Official Amazon Alexa Developer Newsletter _You have total control over when you want Google Home to respond to your voice commands. Its light states tell you the…_madeby.google.com Made by Google (General Google news + Google Home. Subscribe at bottom of page) 🖥 Websites/Sources _Read writing about Alexa. Every day, thousands of voices read, write, and share important stories on Medium about Alexa…_medium.com Alexa - Medium _Read writing about Voice Assistant. Every day, thousands of voices read, write, and share important stories on Medium…_medium.com Voice Assistant - Medium _Read writing about Amazon Echo. Every day, thousands of voices read, write, and share important stories on Medium about…_medium.com Amazon Echo - Medium _Read writing about Google Home. Every day, thousands of voices read, write, and share important stories on Medium about…_medium.com Google Home - Medium _Read writing about Siri. Every day, thousands of voices read, write, and share important stories on Medium about Siri._medium.com Siri - Medium _Read writing about Voice. Every day, thousands of voices read, write, and share important stories on Medium about Voice…_medium.com Voice - Medium venturebeat.com VoiceAssistants_on_VentureBeat _The brain behind Amazon's voice powered devices like Echo, FireTV etc._www.reddit.com Amazon Alexa * /r/alexa _r/AmazonEcho is a community centered around the Amazon Echo, or as we like to call her - Alexa. Alexa is designed…_www.reddit.com Amazon Echo | A voice command system that brings the Internet Of Things to your home * /r… _Everything Google Home: tips, bugs, new features, requests, etc._www.reddit.com Everything Google Home * /r/googlehome _WIRED is where tomorrow is realized_www.wired.com VoiceAssistant _Crunch Network Even before smartwatches, I did not wear a watch. I did not buy an Apple Watch or Pebble, despite the…_techcrunch.com Alexa | TechCrunch _Google Home is Google's answer to Amazon line's of voice-powered Echo devices. After announcing Home at its I/O…_techcrunch.com google home | TechCrunch _Learn about Voice applications, Amazon Alexa and Google Assistant innovation. A hands-free world is coming, join in!_voicelabs.co Blog _multiplex-past, present, future technology research + insights ☂️_readmultiplex.com @ReadMultiplex _Read the latest Amazon Alexa and Google Assistant news, talking about the newest developments in the Voice-First…_voicelabs.co Press Coverage - Voice-First Industry 📜 General news in space (not Voice specific) _Bringing you the latest in Artificial Intelligence, Robotics, and Neurotechnology_inside.com Technically Sentient _Everything about chatbots. From the makers of BotList_botpublication.com BotPublication _Connecting Technology to the Masses_gomainstrm.com GoMainstrm _Chatbots, AI, NLP, Facebook Messenger, Slack, Telegram, and more._chatbotsmagazine.com Chatbots Magazine _Edit description_tinyletter.com Locutius - Letters on Conversational Interfaces by Abi Jones _The O'Reilly Bots Podcast covers advances in conversational user interfaces, artificial intelligence, and messaging…_www.oreilly.com O'Reilly Bots Podcast ideas and resources. — curated by the team Messaging Weekly Smooch — Curated by and the team Chatbots Weekly Omar Pera Reply.ai 🍜 Startups 🗣 Platforms _Actions on Google lets developers build experiences for the Google Assistant._developers.google.com Actions on Google | Actions on Google | Google Developers _Find companies with expertise in designing, developing and optimizing Alexa skills, from agencies and development to…_developer.amazon.com Find Experienced Skill Builders and Tools _I'm open-source, which means you can grab my smarts and put it in a device of your own design. Voice enable your fridge…_mycroft.ai Home - Mycroft _Cortana is your personal assistant, always ready to help you in every situation. See what the world's most personal…_www.microsoft.com Cortana - Meet your personal assistant - Microsoft - Global _Siri on Apple iPhone, iPad and iPod touch lets you use your voice to send messages, make calls, set reminders and more._www.apple.com iOS - Siri - Apple (UK) _Viv is an artificial intelligence platform that enables developers to create an intelligent, conversational interface…_viv.ai Viv 👔 Companies Capito Systems Cognitive Code — Silvia Mindmeld Nuance Verbio ( ) Raven Tech Acq by Baidu Mobvoi ☁️ Cloud Services Amazon Lex Amazon Polly Google Cloud Platform Microsoft Cognitive Services 🛠 Build - SDKs & Frameworks Assist Alexa Skills Kit Pullstring Conversable Bespoken Tools Api.ai for Google Assistant Api.ai for Amazon Alexa Kitt.ai Sayspring Houndify Smartly.ai Gomix IFTTT Mosaic - Extras This post by is a great place to get started: Brian Donohue _Last night betaworks and Amazon hosted the first NYC Amazon Alexa Meetup to bring Alexa owners and enthusiasts together…_medium.com Build your First Alexa Skill AlexaTutorial How to Build your First Amazon Alexa Skill (eBook) by Rocket Insights _Build your first custom skill in just 10 minutes (no programming experience required)._iot-for-all.com Alexa, What’s for Lunch? _At StdLib (“Standard Library”) we allow developers to deploy functions written in Node.js as infinitely scalable API…_hackernoon.com Build an Alexa Skill in 7 Minutes Flat with Node.js and StdLib _Simple builder for Alexa replies._www.npmjs.com alexa-message-builder 💼 Agencies Xandra Assist Rain Mobiquity Matchbox Solstice SciFutures VaynerMedia Witlingo, Inc. AKQA Razorfish Giant Spoon Iconmobile Newscycle Solutions Blink Mindshare TribalScale Volara Vectorform XAPPmedia, Inc. Unified Computer Intelligence Corporation UI Centric Opearlo VocaliD Conversant Labs Future of Voice 📈 Analytics VoiceLabs.co Opearlo Analytics Witlingo, Inc dashbot Botanalytics 🎙 Products Alexa Skills Store App on and iOS Android Unofficial Alexa Skills Store — list of commands that you can ask Google’s voice assistant OK Google Finie 🤖 Hardware Nucleus Jam Voice Ivee Jibo Whyd Kuri Lynx Hello Egg Triby IO Petnet TrackR Musaic Scout Alarm Garageio Toymail ecobee Luma ring Thalmic Labs embodied Owlet Vesper 🤑 Fundraising Alexa Fund Alexa Accelerator, powered by Techstars Lightspeed Ventures Launch Capital NextView Ventures — Betaworks Get Support from the Alexa Team at Betaworks’ Voicecamp _voicecamp is a program for anyone building within the ecosystem of conversational interfaces._betaworks.com voicecamp 💵 Alexa Fund (All the companies announced) Sutro invoxia Petnet Rachio mojio TrackR Musaic Scout Alarm Garageio Toymail Dragon Innovation Kitt.ai ecobee Luma ring Nucleus Defined Crowd Vesper 👥 People & Posts — General Partner . M.G. Siegler GV On Twitter _Vocal computing has a shot at being the next platform — or more — if the big guys don’t screw it up_500ish.com The Voice _“Voice will never be the interaction model,” they say, out loud, to communicate their thoughts._500ish.com Computing in Concert - partner at + runs . Matt Hartman betaworks Hearing Voices Newsletter On Twitter _The rise of services that live in Chatbots, Voice Computing, & Mixed Reality_render.betaworks.com Interfaces On Demand — people-first investor . Sarah Guo Greylock Partners On Twitter _Part 3 in a series on the Conversational Economy_news.greylock.com The Conversational Economy — Voice and the New Era of Multi-Modal Computing — Reporter at TechCrunch. Sarah Perez On Twitter _The next mainstream computing platform may not be bots, AR, or VR, but rather voice-based computing. According to a new…_techcrunch.com 24.5M voice-first devices expected to ship this year, but apps struggle to retain users — vp at . Patrick Montague betaworks On Twitter _Following the success of 2016’s botcamp, betaworks is pleased to announce camps as an ongoing product line. Each year…_render.betaworks.com Announcing Voicecamp — Freelance writer + developer. Owen Williams On Twitter _For decades the technology industry has been chasing the holy grail of computing: natural language conversation. Humans…_medium.com Google Home changed the way I think about voice assistants — CEO Assist. Shane Mac On Twitter _We are excited to announce that the Assist platform is powering one of the first brands on Google Home, Lonely Planet._medium.com Talk to Lonely Planet on Google Home — Senior Product Manager, Intercom. Hugh Durkin On Twitter _When consumer internet arrived in the 1990s, it ushered in a new age of communication. Free internet chat applications…_blog.intercom.com Why voice will be the dominant chatbot interface - Inside Intercom — Partner, . Aaron Batalion Lightspeed On Twitter _When I was a kid, my computer had a SoundBlaster card. If you were a geek like me, you remember editing your autoexec…_medium.com Skate to where the voice is going… — UX / product design . Johna Paolino General Assembly On Twitter _Two Simple User Experience Design Gestures that Delighted a Female User_medium.com Google Home vs Alexa — Trying to build a better company, every day and . Adam Marchick @VoiceLabsCo Kahuna — Co-Founder / EIR @ The Chernin Group. Alexandre Linares @VoiceLabsCo On Twitter _The Voice Report starts with the underlying hardware devices and works its way up the voice-first stack_read.acloud.guru The 2017 Voice Report — CEO and CoFounder, PullString. Prev, Pixar. Oren Jacob On Twitter — Founder + Editor at . Brian Roemmele Multiplex On Twitter _During the early computer era of the 1960s, it was thought there would only be the need for a few dozen computers. By…_techpinions.com There is A Revolution Ahead and It Has A Voice _“Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans”–Apple…_medium.com Apple’s Secret AI Technology: Meet Vocal IQ the self learning technology that is a part of Siri2. — Invented the hashtag; X Uber; Xoogler. Chris Messina On Twitter — Director of User Experience . Author of the O’Reilly book Designing Voice User Interfaces. Cathy Pearl @Sense_ly On Twitter _Edit description_www.amazon.com Designing Voice User Interfaces: Principles of Conversational Experiences — Strategically-oriented product design leader . Trip ODell @Amazon On Twitter _Several times a week, my children host an evening dance party in the living room. The playlist features all the modern…_medium.com Velveteen Rabbits: What a Children’s Story Can Teach Us About Computers that Talk. — Co-founder & Partner at NextView Ventures. David Beisel On Twitter _In the three months since I penned my initial blog post on "Ubiquity of Voice and the Venture Opportunity," I've been…_genuinevc.co Charting the Personal Voice Computing Startup Roadmap - GenuineVC Nithya Thadani — CEO of Rain _Last October, New York-based digital agency Rain worked with Campbell's to find a new way to push out the CPG giant's…_www.adweek.com How This Agency Built Its Own App Using Amazon Echo —I’m an Innovation-Obsessed Founder at Mylestone. Dave Balter On Twitter _Why Voice Assistants may be the answer you’ve been looking for._medium.com “Alexa, How Can I Get Unfair Ecosystem Advantage” — Partner at Lightspeed Venture Partners. Jeremy Liew On Twitter _Games have been a killer app for just about every new platform, from PCs to TVs (via game consoles) to Facebook to…_medium.com Games for Alexa — Co-Founder/CEO Siri & Viv Labs. Dag Kittlaus On Twitter _Why Viv is Joining Forces with Samsung_elevate.samsungnext.com The Path to Intelligence Everywhere — Co-founder of . Jan König HashtagNow On Twitter _Thoughts on Designing Seamless Voice Experiences_medium.com Alexa, Please Send This To My Screen 🚀 - A community helping facilitate connections to; I am working on an experiment - Get a skill made/make skills for people/companies- Find investors active in the field- Intros to other active enthusiasts- Bounce ideas around with others- Advice & mentorship from experienced individuals- Resources and tools to help you build- Discover interesting products and companies 👍 Please tap “♥︎” if you found this useful to help others see it too 👾 This post is also on GitHub and open for suggestions, just submit a pull request 👉 Feel free to follow and reach out on Twitter 🙏 Thanks to everyone who looked at this draft very early on! And perhaps I’ll see you all in the newsletter or 😉 Build Voices Side Note: I have ‘borrowed’ this template from which is an awesome post & newsletter I use to learn about Machine Learning. Thanks The Non-Technical Guide to Machine Learning & Artificial Intelligence Sam DeBrule 🙌

Ultimate Guide to Voice Assistants

A System… Complex Systems The macrosystems around us (energy, health, food, water) are grand in their scale and interrelated at levels that we are still trying to grasp. Despite our little but growing understanding of complex systems, we know that two things happen when they change: 1. The changes are nonlinear and the effects are oftentimes exponential 2. The changes affect more than the individual system we are studying Agriculture is a system that we know how to deal with since we understand the convergence of its inputs such as seed, land, soil quality, water, human capital etc. In , Donella Meadows calls ‘ . The elements (land, seed, water), interconnections (we plant the seeds, we water the seeds, there is a cycle of death before growth, harvest etc.) and the purpose (to feed people with the harvest) are all clear in agriculture. As we’ve industrialized, i.e. made changes to the complex agricultural system, we’ve seen the effects in the other complex systems like the job market, health (diseases from inorganic foods), weather (droughts) at the same time as we’ve seen the benefits. But we have come to realize the interconnectedness of the agricultural system with everything else we pay attention to. Thinking in Systems: A Primer a system an interconnected set of elements coherently organized in a way that achieves something . . . consisting of three parts: elements, interconnections, and a function or purpose The Utility System The utility is on the cusp of change, faster than the industry is prepared for or it has ever had to deal with. The utility that delivers our electricity has always favored stability over agility. This has enabled the utility to provide you and I power in a stable, safe and reliable way. There was a time when we valued that unconditionally. We had a contract, both physical and implied, that the utility would supply us with electricity when we needed it and we would pay for that electricity when we got the bill. The government, through policy and regulation, helped to maintain that contract. Things were fine. But that is changing. The utility now has competition from Tesla, Google and telecom companies. The pace of this change is partly due to ; smart meters, sensors, the (IoT and IIoT) and intelligent machines in our homes and buildings means there is more two-way flow of information. rapid digitization (another complex system that is having non-linear and exponential effects on other complex systems) Internet of Things The utility is also seeing changes due to competition from the construction industry who are bucking convention and constructing buildings in ways that totally remove the need for a utility’s services. A residential example is the (image below), and on the city scale . They are changing the concept of a distant and separate utility provider by incorporating all utility services (water, telecoms and power) as part of the embedded within their buildings.. Kasita home being built by a company in Austin , we have the Songdo Smart city system Model of several modules of the Kasita Home The Home As A Utility SubSystem If the utility system as a whole is digitizing, the evidence of this is even more apparent in how quickly our homes are going through this rapid digitization. This is playing out in the form of the connected home. The connected home is simply a network that enables the operations and interconnections of multiple devices and products in the home. In laymen’s terms, it’s a home that is computerized. It’s a Jetsons home. Traditional classifications of the devices in the home and use cases for connected devices (connected toothbrush anyone?) miss that consumers want just the basic things in their homes. The devices and their interoperability is currently packaged as networking, media, entertainment, energy usage and efficiency etc. What these terms miss is that the consumer does not talk in terms of ‘I want my home networked’. Rather, the average consumer will say ‘Is the home alarm on?’ as they go to bed. It’s the feeling of safety and security in their abode that they desire. The connection is not as important as the home in this equation. Image courtesy of CBInsights. T . We’ve lost that point though. Google Home, Nest Protect, Amazon Echo, Ring, August Lock, Leeo, Sonos, Plum, Sevenhugs, Canary, KamarQ, Sentry, Pwety, Latch, Wigwag, Edyn, Ivee, Rachio, Ecovent, Nanit, There, Beddit etc. The list of products that are vying for space in your connected home grows each day. Some absolutely pointless. Actually, most actually pointless. There is no empathy embedded in these products. Just business models. Note: one of those products up there does not exist. But you wouldn’t have known if I didn’t mention it. There are that many random products in the market today. he connected home is truly, and should really just be, a home that provides safety, comfort and convenience to the homeowner through the use of technology Long Term Systems Thinking If we agree the sum of these individual separated parts never equals the whole, why do we still focus on breaking things down into their component parts to get a better understanding of situations, companies and systems? Because we are focused on the short term. Analysis, which is really reductionism, robs us of our ability to critically think about whole systems. The companies building connected products for the home are missing the whole in pursuit of the ‘one’ thing they have to sell. And it’s further eroding the consumer’s ability to consider the bigger picture, especially with the complex and ambiguous systems that we’ve explored above, since it’s the easy thing to do. The signs suggest we won’t be doing much better in our near-term decision and policy making either. So what’s a possible solution? Big Bang Disruption Larry Downes and Paul Nunes, in their book, suggest that ‘ ’ differ from more traditional innovations not just in degree, but in kind. These disruptions are more inventive, better integrated with other services and products (for example taking a platform instead of a product approach) and that these disruptions take advantage of the customer’s access to more information about the product and their ability to share and contribute to the utilization of that product. This sounds exactly like some of the technologies that will be discussed later in this article and most especially sounds like the current state with Distributed Energy Resources (DERs), which I will not discuss in much detail. The changes caused by the big bang disruption might not be full replacements, as there will still be a need for a generation source, but the disruption might come in the form of engagement with the physical assets — e.g. a user managing their Powerwall electricity usage with the aid of . Big Bang Disruptions Artificial Intelligence and selling excess power through the blockchain How do big bang disruptions happen? They tend to follow a path of 1. : where the work is going on outside of the current constraints, e.g. regulatory, of the incumbents. Unencumbered development by the disruptor 2. : where the traditional product life cycle is shortened. The adoption curve looks different from the traditional early adopter, early majority, late majority to laggard curve. The new adoption path looks more like a straight line which heads up and then drops off once the market is saturated. Unconstrained growth 3. : unlike the stepwise strategic approach of the incumbent, an approach that would normally work, the disruptor tends to take a more undisciplined approach to product development. This enables the disruptor to bypass the more traditional approach of picking one of lower cost, constant innovation or customized offerings and try to implement all three strategies from the launch of their product; a better performing product customized to the customer need and sold at a lower price. This causes strategic confusion for the incumbent, or in our case the utility, who does not know how to respond to this competitive threat. Undisciplined strategy The Antifragile Utility: Recognizing The Disruption. Since the utility is my main focus, and since the work of the utility is now converging with the sustainable built environment movement, how do we get back to the system approach to thinking about the future of this industry? And in particular, directing our utilities and resources a little bit more (shall we say) towards a long-term focus? It’s actually quite simple. It’s by the utilities becoming , or a concept I’m calling it the anti-fragile grid. Like the natural systems it mimics, a sustainable farm is always a polyculture and depends on the synergies between its various components from soil microbes to animals. learning organizations Tesla Model S: A platform, not just a product : The main news about Autonomous EVs is the amount of electricity they’ll consume — . What the pundits miss is the anti-fragile system capacity that comes as a result of many autonomous vehicles operating and gathering data, data that becomes valuable for improving the whole system. This concept is called . In laymen’s terms; every autonomous vehicle that is driving thousands of the miles on the road is gaining knowledge, through machine learning, that improves the collective knowledge of every autonomous vehicle out there. When one autonomous vehicle experiences a shock, say an accident, even though the vehicle might have a little damage, the collective whole (the autonomous vehicle knowledge database) learns and improves. One vehicle, a node in the system, might have failed, but the whole system (adaptive system) has grown stronger from the shock to that node. Now replace the ‘autonomous vehicle’ node in the transport system with a ‘Tesla roadster/Tesla Powerwall/Solarcity panel’ node on an anti-fragile grid. The same antifragility can be achieved, where a shock to one Tesla/Solarcity node does not cause the whole system, or electric grid, to fail. In fact, the whole grid learns from the failure of that node and grows stronger by learning to allocate resources dynamically. Borrowing from the transportation industry (Tesla in particular) 2,701 terawatt-hours, or an 8 percent increase to global annual electricity demand by 2040 swarming Another part of this change should be in the utility’s approach to building capacity. Due to a design flaw in the utility system, the industry currently overbuilds. Generation projections are made years in advance to cater to expected customer demand and a best guesstimate about what utility costs and subsequent customer rates will be for electricity during peak periods in the future. While this is long-term thinking, it takes 5–6 years to plan and build a power plant, missing all the signals required when you are thinking in systems. This is siloed thinking focused on just the business requirements of the utility. Instead, the utility can benefit by that enables all the product providers (that long list at the start of this article) to provide system , while using the utility’s platform. The way the platform works is that, like agriculture, it forces the utility to focus on the purpose of the system; to enable the consumer to live comfortably and safely in their homes using energy. becoming a platform provider flexibility Connected Water Quality product/platform with ‘Clean Water’ As the Purpose (Image: Axis Design) Until there is a clear role for the utility (and whatever it chooses as its product) within this converging new system, consumers will continue to lose. The utility industry is about to get its lunch eaten by the most unexpected of competitors, as it is the nature of big bang disruptions, because of this unwillingness to think well beyond its current fat balance sheet. Heeding this warning and doing something about it now will determine the long term (and even midterm) existence of most of the utilities that we see around us today. Your thoughts? My team and I provide product marketing to energy and tech companies through Harper Jacobs & utility consulting at Asha Labs . And buy 40 Semi-Obvious (Startup) Lessons . Sign up for my Polymathic Monthly Newsletter here , I guarantee you’ll love it. Please tap that heart below if you liked the article. It helps other people see the story, and it helps me know you’d like to see me write more (we all need some validation :)).

Convergence of Systems: Utilities, The Built Space and Transportation.

HackerNoon: What is your company in 2–5 words? Erik Huberman: AI Enabled. Tech-Integrated. Marketing Powerhouse. Why is now the time for your company to exist? Now more than ever, Hawke Media’s existence is crucial because we are celebrating a decade of marketing excellence and leading the way in the AI-integrated marketing landscape. As the fastest growing agency in the nation, our expertise in artificial intelligence and data analytics sets us apart. Our proprietary platform, Hawke AI, has been developed over nearly ten years and is at the core of our strategy. It delivers deep audience insights and competitive analysis, empowering us to craft highly targeted and adaptive marketing campaigns. By automating tasks and enhancing decision-making, Hawke AI analyzes extensive data from over 7,000 brands and $500 million in ad spend. Operating in real-time, it dynamically adjusts to market changes and ensures transparency across all major marketing channels, positioning us at the forefront of the industry. What do you love about your team, and why are you the ones to solve this problem? If there was one thing to celebrate over the past 10 years at Hawke Media, it would be our people. As a CEO and founder, I've quickly learned that it's all about people. Creating an environment where you can develop, hire, attract, and retain great people is critical to building a great business. Their incredible marketing capabilities and talents are what make Hawke Media the powerhouse it is today. With innovation being crucial in our ever-evolving world, I've witnessed firsthand how many of our competitors have fallen apart. My team at Hawke Media goes above and beyond in identifying potential disruptions and adapting to them, allowing us to stay on top of trends and making Hawke Media the leading marketing agency of choice. If you weren’t building your startup, what would you be doing? I would be building another one! At the moment, how do you measure success? What are your metrics? Our success metrics are directly tied to specific ROI indicators, such as revenue increases, customer lifetime value, and engagement metrics. To date, Hawke Media boasts 10 consecutive years of profitability, over $2.9 billion in gross revenue, and has never raised debt or outside funding. Our success is also marked by growing 4,755 brands, 90+ awards for innovation, 44 angel investments, and 13 strategic acquisitions. As we celebrate 10 years, our 2,957 partnerships reflect our ongoing commitment to transforming marketing for businesses of all sizes. In a few sentences, what do you offer to whom? Hawke Media offers best-in-class marketing services to both established brands and burgeoning businesses. Our comprehensive offerings include strategy development, branding and production, media buying, web design, content and social media management, lifecycle marketing, photo and video production, affiliate marketing, and Amazon services. We create digital playbooks tailored to your business, develop unique brand aesthetics, and run data-driven campaigns to target ideal consumer touchpoints. Our goal is to help brands exceed their marketing goals and drive massive revenue through customized growth strategies. What’s most exciting about your traction to date? The most exciting aspect of Hawke Media's success to date is our remarkable growth, both as an agency and in the growth we've achieved for our clients. We've had the privilege of working with 4,755 brands including Crocs, Casamigos, Barstool Sports and more, helping them reach new heights they might have never envisioned for themselves. Our commitment to driving client success has been a key factor in our own growth, as we continually strive to exceed expectations and deliver exceptional results. This mutual growth is a testament to our innovative strategies, dedicated team, and the strong partnerships we've built with our clients. Where do you think your growth will be next year? Currently we are in growth and expansion mode at Hawke Media. We have doubled down in Mergers and acquisitions, software and tech investments, and are anticipating exponential growth in all verticals over the next year. Tell us about your first paying customer and revenue expectations over the next year. My first paying customer was a company that approached me after I sold my last business. Initially, they wanted to hire me full-time, but I wasn't interested in a full-time job. Instead, I offered to consult for them one day per week. They insisted on three days, and after some negotiation, we agreed on a part-time schedule of three days per week. This arrangement was pivotal as it gave me the foundation to start Hawke Media. Regarding revenue expectations for the next year, we anticipate expeditious growth. Our goal is to achieve a significant increase in revenue through expanding our client and employee base, enhancing our service offerings, and leveraging our expertise in marketing. What’s your biggest threat? The biggest threat currently is AI. Rapid disruption in our space means artificial intelligence will change and automate much of what we do. However, every threat is also an opportunity. I strongly believe we are taking the right steps to benefit from this trend, while our competitors might not keep up. Hawke AI is a key part of our strategy to stay ahead and leverage these advancements. By analyzing marketing and revenue data from more than 7,000 brands, over $500 million in media spend, and providing universal transparency across every major channel, we can(and are) turn this potential threat into a significant opportunity. HackerNoon : What is your company in 2–5 words? HackerNoon Erik Huberman : AI Enabled. Tech-Integrated. Marketing Powerhouse. Erik Huberman Why is now the time for your company to exist? Now more than ever, Hawke Media’s existence is crucial because we are celebrating a decade of marketing excellence and leading the way in the AI-integrated marketing landscape. As the fastest growing agency in the nation, our expertise in artificial intelligence and data analytics sets us apart. Our proprietary platform, Hawke AI, has been developed over nearly ten years and is at the core of our strategy. It delivers deep audience insights and competitive analysis, empowering us to craft highly targeted and adaptive marketing campaigns. By automating tasks and enhancing decision-making, Hawke AI analyzes extensive data from over 7,000 brands and $500 million in ad spend. Operating in real-time, it dynamically adjusts to market changes and ensures transparency across all major marketing channels, positioning us at the forefront of the industry. What do you love about your team, and why are you the ones to solve this problem? If there was one thing to celebrate over the past 10 years at Hawke Media, it would be our people. As a CEO and founder, I've quickly learned that it's all about people. Creating an environment where you can develop, hire, attract, and retain great people is critical to building a great business. Their incredible marketing capabilities and talents are what make Hawke Media the powerhouse it is today. With innovation being crucial in our ever-evolving world, I've witnessed firsthand how many of our competitors have fallen apart. My team at Hawke Media goes above and beyond in identifying potential disruptions and adapting to them, allowing us to stay on top of trends and making Hawke Media the leading marketing agency of choice. If you weren’t building your startup, what would you be doing? I would be building another one! At the moment, how do you measure success? What are your metrics? Our success metrics are directly tied to specific ROI indicators, such as revenue increases, customer lifetime value, and engagement metrics. To date, Hawke Media boasts 10 consecutive years of profitability, over $2.9 billion in gross revenue, and has never raised debt or outside funding. Our success is also marked by growing 4,755 brands, 90+ awards for innovation, 44 angel investments, and 13 strategic acquisitions. As we celebrate 10 years, our 2,957 partnerships reflect our ongoing commitment to transforming marketing for businesses of all sizes. In a few sentences, what do you offer to whom? Hawke Media offers best-in-class marketing services to both established brands and burgeoning businesses. Our comprehensive offerings include strategy development, branding and production, media buying, web design, content and social media management, lifecycle marketing, photo and video production, affiliate marketing, and Amazon services. We create digital playbooks tailored to your business, develop unique brand aesthetics, and run data-driven campaigns to target ideal consumer touchpoints. Our goal is to help brands exceed their marketing goals and drive massive revenue through customized growth strategies. What’s most exciting about your traction to date? The most exciting aspect of Hawke Media's success to date is our remarkable growth, both as an agency and in the growth we've achieved for our clients. We've had the privilege of working with 4,755 brands including Crocs, Casamigos, Barstool Sports and more, helping them reach new heights they might have never envisioned for themselves. Our commitment to driving client success has been a key factor in our own growth, as we continually strive to exceed expectations and deliver exceptional results. This mutual growth is a testament to our innovative strategies, dedicated team, and the strong partnerships we've built with our clients. Where do you think your growth will be next year? Currently we are in growth and expansion mode at Hawke Media. We have doubled down in Mergers and acquisitions, software and tech investments, and are anticipating exponential growth in all verticals over the next year. Tell us about your first paying customer and revenue expectations over the next year. My first paying customer was a company that approached me after I sold my last business. Initially, they wanted to hire me full-time, but I wasn't interested in a full-time job. Instead, I offered to consult for them one day per week. They insisted on three days, and after some negotiation, we agreed on a part-time schedule of three days per week. This arrangement was pivotal as it gave me the foundation to start Hawke Media. Regarding revenue expectations for the next year, we anticipate expeditious growth. Our goal is to achieve a significant increase in revenue through expanding our client and employee base, enhancing our service offerings, and leveraging our expertise in marketing. What’s your biggest threat? The biggest threat currently is AI. Rapid disruption in our space means artificial intelligence will change and automate much of what we do. However, every threat is also an opportunity. I strongly believe we are taking the right steps to benefit from this trend, while our competitors might not keep up. Hawke AI is a key part of our strategy to stay ahead and leverage these advancements. By analyzing marketing and revenue data from more than 7,000 brands, over $500 million in media spend, and providing universal transparency across every major channel, we can(and are) turn this potential threat into a significant opportunity.

"As a CEO and Founder, I've Quickly Learned that It's All About People." says Hawke Media Founder

"እንደ ዋና ሥራ አስፈፃሚ እና መስራች ፣ ሁሉም ነገር በሰዎች ላይ መሆኑን በፍጥነት ተማርኩ ።" ይላል ሃውክ ሚዲያ መስራች

"Como director ejecutivo y fundador, aprendí rápidamente que todo es cuestión de personas", dice el fundador de Hawke Media

"zuzendari nagusia eta sortzailea naizen aldetik, azkar ikasi dut jendeari buruz dela". dio Hawke Media Fundatzaileak

「CEO兼創業者として、私はすぐに、すべては人に関することだと学びました」とホークメディアの創業者は語る。

«Бас директор және негізін қалаушы ретінде мен бәрі адамдарға қатысты екенін тез білдім». дейді Hawke Media негізін қалаушы

"CEO이자 창립자로서 저는 모든 것이 사람에 관한 것이라는 것을 빨리 깨달았습니다." Hawke Media 창립자의 말입니다.

"Amin'ny maha-Tale Jeneraly sy Mpanorina ahy, dia nianatra haingana aho fa momba ny olona izany." hoy ny mpanorina ny Hawke Media

„Ca CEO și fondator, am învățat rapid că totul este despre oameni.” spune fondatorul Hawke Media

"Som VD och grundare har jag snabbt lärt mig att det handlar om människor." säger Hawke Media grundare

"ஒரு CEO மற்றும் நிறுவனர் என்ற முறையில், இது மக்களைப் பற்றியது என்பதை நான் விரைவாகக் கற்றுக்கொண்டேன்." ஹாக் மீடியா நிறுவனர் கூறுகிறார்

"Bosh direktor va asoschi sifatida men hamma narsa odamlarga tegishli ekanligini tezda bilib oldim." - deydi Hawke Media asoschisi

Hawke Media 创始人表示：“作为首席执行官和创始人，我很快就意识到，一切都与人有关。”

In 2020, I authored an article on LinkedIn titled "Welcome to Edge Territory." (Welcome to Edge Territory – the Hidden Space Between Networks | LinkedIn) The blog was intended to start a series exploring the complexities of edge computing. The idea still intrigues me, and I am considering revisiting it—perhaps as a podcast series. One of the more startling insights from that blog was the projected $10 trillion in damages by 2025, a figure we are now on track to exceed by the end of 2024. Despite $300 billion being spent a year on prevention, this exponential growth in damage continues to outpace our efforts. I defined "edge territory" as "the unmapped space beyond the network edge between environments, where secured and unsecured networks and devices collide." I still find that definition fitting, though I would add that we continually discover new edges beyond what was previously understood. These evolving threats extend beyond manageable devices to unmanaged IoT and edge scenarios in cloud and data center deployments. So, the critical question becomes: Where can I find the edge? The edge is everywhere, constantly shifting based on how we use new computing concepts and remain productive in our daily lives, individually and organizationally. This dynamic presents a challenge that I highlighted in that earlier blog. The seen and unseen spaces at the edge invite us to cooperate more closely as a community and marketplace. I am thrilled to collaborate with other leaders working tirelessly to provide solutions for visibility and response in edge scenarios. Both attackers and defenders are keenly aware of how vulnerable we are. Since 2020, the number of known exploits has grown exponentially. The challenge posed by bounties and threat hunting has been met with increasingly sophisticated tools, making discovery more effective for attackers and cybersecurity teams. One article noted that quarterly disclosed additions to the Common Vulnerabilities and Exposures (CVE) database surged from 8,051 in 2021 to 26,447 in 2022—a staggering 320% year-over-year increase. By January 2024, the CVE database had reached 176,000 entries; as I write this, the number surpassed 240,000. What stands out about the edge is how exponential growth is clear across the board: in losses, spending, and the number of identified vulnerabilities. Addressing cybersecurity at the edge requires finding the necessary solutions for visibility and response. I want to take a moment to acknowledge and express gratitude to the many vendors, service providers, and companies on the front lines of what can only be described as a war zone in edge territory. A comprehensive approach to edge security might involve intrusion detection systems, Security Operations Centers (SOCs), firewalls, security system management, endpoint management solutions, log management solutions, event management solutions, and strategies for decreasing time for responding to an event that is detected by a tool or professional. I also want to highlight the incredible leaders and solutions in the Extended Detection and Response (XDR) space. They focus on device vulnerabilities and work diligently to reduce the meantime to detect and contain threats, using AI and other advanced technologies. For those on the front lines, I hope to bring more awareness to the sheer volume of activity and effort needed to stay ahead of the identified exploits that threaten organizations and individuals. Malicious actors' use of AI or Machine Learning Models (MLLs) is a growing concern, underscoring that edge territory is constantly evolving. A comprehensive approach to edge cybersecurity should begin with network awareness and extend to every connected device. This is a daunting challenge, as most organizations struggle to gather the necessary tools and ability to optimize awareness and response. Recent reports, such as one from Google’s Mandiant, show that the average dwell time—the time it takes to detect a cyber intrusion—has dropped to a record low of 2.24 months. As we continue to navigate edge territory, we, as a community, are working together more effectively to observe, identify, protect, and respond. This collective effort can potentially reduce the exponential growth of damage and chart a different course for the future. Recent reports, like Sophos' 2024 State of Ransomware in Healthcare, highlight the rapid increase in attacks on healthcare organizations, with incidents rising from 34% in 2021 to 67% in 2024. These statistics serve as a stark reminder that edge territory is expanding and becoming increasingly dangerous. Combined attack vectors or surface information offers a holistic view of edge territory. At the network level, monitoring vulnerabilities and traffic allows for responses. At the device level, observability from the network through the application and data layers covers every aspect of edge territory. One reason the Edge continues to evolve, and grow is the expansion of connected services and digital assets. As one analyst from Silicon Angle recently noted, "The edge is now space." I am excited to join my team in applying AI more holistically across edge-to-edge scenarios, offering greater visibility and empowering organizations to respond faster than ever with more connected analytics. With our DCX Offering, we have extended our awareness edge-to-edge and now provide automated detection and containment through isolation. This adds value to any existing solution, creating unprecedented metrics for success, with over 240,000 incidents detected and contained last year alone. We are proud to collaborate with writers and industry experts to provide our partners, vendors, and industry leaders with improved awareness of edge territory making the undefinable visible and approachable for any organization.                                                                   Follow Our Blog & News https://guarddog.ai/news/ In 2020, I authored an article on LinkedIn titled "Welcome to Edge Territory." ( Welcome to Edge Territory – the Hidden Space Between Networks | LinkedIn ) The blog was intended to start a series exploring the complexities of edge computing. The idea still intrigues me, and I am considering revisiting it—perhaps as a podcast series. Welcome to Edge Territory – the Hidden Space Between Networks | LinkedIn One of the more startling insights from that blog was the projected $10 trillion in damages by 2025, a figure we are now on track to exceed by the end of 2024. Despite $300 billion being spent a year on prevention, this exponential growth in damage continues to outpace our efforts. I defined "edge territory" as "the unmapped space beyond the network edge between environments, where secured and unsecured networks and devices collide." I still find that definition fitting, though I would add that we continually discover new edges beyond what was previously understood. These evolving threats extend beyond manageable devices to unmanaged IoT and edge scenarios in cloud and data center deployments. So, the critical question becomes: Where can I find the edge? The edge is everywhere, constantly shifting based on how we use new computing concepts and remain productive in our daily lives, individually and organizationally. This dynamic presents a challenge that I highlighted in that earlier blog. The seen and unseen spaces at the edge invite us to cooperate more closely as a community and marketplace. I am thrilled to collaborate with other leaders working tirelessly to provide solutions for visibility and response in edge scenarios. Both attackers and defenders are keenly aware of how vulnerable we are. Since 2020, the number of known exploits has grown exponentially. The challenge posed by bounties and threat hunting has been met with increasingly sophisticated tools, making discovery more effective for attackers and cybersecurity teams. One article noted that quarterly disclosed additions to the Common Vulnerabilities and Exposures (CVE) database surged from 8,051 in 2021 to 26,447 in 2022—a staggering 320% year-over-year increase. By January 2024, the CVE database had reached 176,000 entries; as I write this, the number surpassed 240,000. What stands out about the edge is how exponential growth is clear across the board: in losses, spending, and the number of identified vulnerabilities. Addressing cybersecurity at the edge requires finding the necessary solutions for visibility and response. I want to take a moment to acknowledge and express gratitude to the many vendors, service providers, and companies on the front lines of what can only be described as a war zone in edge territory. A comprehensive approach to edge security might involve intrusion detection systems, Security Operations Centers (SOCs), firewalls, security system management, endpoint management solutions, log management solutions, event management solutions, and strategies for decreasing time for responding to an event that is detected by a tool or professional. I also want to highlight the incredible leaders and solutions in the Extended Detection and Response (XDR) space. They focus on device vulnerabilities and work diligently to reduce the meantime to detect and contain threats, using AI and other advanced technologies. For those on the front lines, I hope to bring more awareness to the sheer volume of activity and effort needed to stay ahead of the identified exploits that threaten organizations and individuals. Malicious actors' use of AI or Machine Learning Models (MLLs) is a growing concern, underscoring that edge territory is constantly evolving. A comprehensive approach to edge cybersecurity should begin with network awareness and extend to every connected device. This is a daunting challenge, as most organizations struggle to gather the necessary tools and ability to optimize awareness and response. Recent reports, such as one from Google’s Mandiant, show that the average dwell time—the time it takes to detect a cyber intrusion—has dropped to a record low of 2.24 months. As we continue to navigate edge territory, we, as a community, are working together more effectively to observe, identify, protect, and respond. This collective effort can potentially reduce the exponential growth of damage and chart a different course for the future. Recent reports, like Sophos' 2024 State of Ransomware in Healthcare, highlight the rapid increase in attacks on healthcare organizations, with incidents rising from 34% in 2021 to 67% in 2024. These statistics serve as a stark reminder that edge territory is expanding and becoming increasingly dangerous. Combined attack vectors or surface information offers a holistic view of edge territory. At the network level, monitoring vulnerabilities and traffic allows for responses. At the device level, observability from the network through the application and data layers covers every aspect of edge territory. One reason the Edge continues to evolve, and grow is the expansion of connected services and digital assets. As one analyst from Silicon Angle recently noted, "The edge is now space." I am excited to join my team in applying AI more holistically across edge-to-edge scenarios, offering greater visibility and empowering organizations to respond faster than ever with more connected analytics. With our DCX Offering, we have extended our awareness edge-to-edge and now provide automated detection and containment through isolation. This adds value to any existing solution, creating unprecedented metrics for success, with over 240,000 incidents detected and contained last year alone. We are proud to collaborate with writers and industry experts to provide our partners, vendors, and industry leaders with improved awareness of edge territory making the undefinable visible and approachable for any organization.                                                                   Follow Our Blog & News https://guarddog.ai/news/ https://guarddog.ai/news/

The Edge: How Do I Know I’ve Found It?

প্রান্ত: আমি কিভাবে জানব যে আমি এটি খুঁজে পেয়েছি?

The Edge: Woher weiß ich, dass ich es gefunden habe?

The Edge: ¿Cómo sé que lo he encontrado?

The Edge : Comment savoir si je l’ai trouvé ?

किनारा: मैं कैसे जानूँ कि मैंने उसे पा लिया है?

エッジ: 見つけたかどうかはどうすればわかるのでしょうか?

The Edge: 찾았는지 어떻게 알 수 있을까?

The Edge: Como sei que o encontrei?

Грань: как я узнаю, что нашел ее?

The Edge: Onu Bulduğumu Nasıl Anlarım?

The Edge: Làm sao tôi biết mình đã tìm thấy nó?

边缘：我怎么知道我找到了它？

Hello Everyone! After a period of absence from writing, I'm back, trying to get back into the swing of things. I want to emphasize that the experiences shared in this space are based on my academic and professional experiences. Therefore, it is important to remember that what is described here may only represent a fraction of reality and should not be interpreted as a definitive formula for specific processes, procedures or services. I am currently very excited about this new phase of my career. I have learned a lot and would like to share some of this journey with the community. I hope that the information presented here will be of great value to readers. People First - The importance of Soft Skills When I participated in my first selection process, a few years ago, I clearly remember the almost boring steps I went through: interview with HR, practical test, interview with the technical leader and, finally, interview with the manager. Throughout my career as a developer, I have participated in several interviews with different models. At that time, I always felt uncomfortable interviewing with HR people. I didn’t quite understand why, thinking: “If I can do what is required in the technical test, I am already showing enough competence for the position.” When I took on my role as technical development leader, one of my responsibilities was to collaborate with HR (yes, the same people with whom I didn't understand the reason for participating in the selection process) in preparing a technical test and defining the interview format for two candidates starting in the backend area. I thought I already knew what a beginner developer in the backend area should deliver and what would be considered a differentiator in the test. However, what I didn't expect was that, despite the importance of the code, other demands arose beyond project delivery: how to evaluate candidates in terms of communication? What is their interest in the position? And how can the context they present influence their suitability for the proposed position? These and other questions turned out to be as relevant as the code presented by both candidates, something I had not previously considered in my early years as a developer. I remember sitting at the meeting table to make the final decision and being a little surprised to realize how little was discussed about each candidate's technical skills. Part of this was due to the fact that they were entry-level candidates, so it was to be expected that their technical skills would not be as developed, and this was not the main focus of the discussion. However, even for more advanced vacancies, especially for senior-level positions, it is crucial to consider skills such as communication, documentation, adaptability, proactivity and other skills often mentioned. These soft skills are fundamental and can be decisive for success in the role, in addition to technical skills. In fact, this is my next point. The line between Junior and Senior (No, not mid-level). I know there's a lot of discussion about the meaning and classification of terms related to experience levels, like "senior." Some say that "senior is defined by years of experience", others claim that "in some companies, you gain senior experience after a year". There are also those who say that "there is no clear distinction between junior and senior" or that "seniors only do code reviews and approve PRs". Some of these statements are comical, others have a grain of truth. The fact is that the concept of "senior" is quite varied and it is not up to me to define a universal standard, but I can offer some guidance to understand this classification in a more individual way. Being a senior is not just about technical knowledge, although this is undoubtedly very important. A true senior, or at least a good senior, is someone capable of solving complex problems in terms of both code and systems architecture. Maintaining code quality, following good development practices and having knowledge of project management are crucial aspects. The key difference is that a senior must be able to execute all of this autonomously and, more importantly, collaborate with teams from different levels and sectors to deliver the best project possible. Furthermore, a real senior (or at least the best ones) not only leads and guides the team, but also develops and prepares other developers to take on new positions and responsibilities. My first experience leading a project When I took on my first project, my boss knew that I hadn't previously led any other project. I just participated in the development and worked out some things that would facilitate development in terms of communication with management. The first question he asked me was: "How many people and what kind of will be enough to complement the project." I didn't know the answer right away, it was a very complex question. Because the project was only in the outline, we had no idea of ​​the stack, how much time it would take to complete each task and other metrics of interest to the people above. I did a complete study to be able to deliver the next day on several project management methodologies: Pert, Planning Poker We collaboratively chose the one that was best suited and the challenge began. for each member of the team, what is the best development platform, what is the best stack to use, how the system architecture will work, studying other solutions on the market, monitoring the level of each developer, meetings, meetings and more meetings with the management. When I least realized it, I was increasingly distant from the code. My role became to suggest improvements and fix some critical bugs so that the project could work, or at least provide a solid foundation for the developers to start. The rest of the work involved communicating with the developers, dividing tasks, monitoring of metrics and, basically, one eye on Asana (to estimate project delivery time) and another on Meet to make sure my microphone wasn't on and nothing unwanted was "accidentally" slipped through. Conclusion and a look at the past - to the master with affection I started my career as a development intern and, interestingly — and you might find it a little contradictory on my part — I didn't have any concrete experiences (at least not formally recorded in my employment record) that would classify me as a junior, full or senior developer. Much of the experience I gained came from personal projects and research at college. It was a gradual process until I realized that my skills had evolved since those early days. But yes, I worked intensely as a developer at different levels and had the opportunity to meet different types of senior professionals throughout my career: The very competent and effective senior, but uncommunicative, who solved problems without providing explanations about his approach.
The senior is excellent at communication and teaching, but often overwhelmed with urgent tasks and no time to teach.
The senior who was enthusiastic about over-engineering and centralizing technology, but who met deadlines and delivered what he promised. The most important thing is that, despite their justifiable flaws (although it is possible, it is very difficult to balance demands), all of these professionals had something valuable to teach. These experiences helped shape my career and gave me a clear view of what works and what doesn't in systems development. Hello Everyone! After a period of absence from writing, I'm back, trying to get back into the swing of things. I want to emphasize that the experiences shared in this space are based on my academic and professional experiences. Therefore, it is important to remember that what is described here may only represent a fraction of reality and should not be interpreted as a definitive formula for specific processes, procedures or services. Hello Everyone! After a period of absence from writing, I'm back, trying to get back into the swing of things. I want to emphasize that the experiences shared in this space are based on my academic and professional experiences. Therefore, it is important to remember that what is described here may only represent a fraction of reality and should not be interpreted as a definitive formula for specific processes, procedures or services. I am currently very excited about this new phase of my career. I have learned a lot and would like to share some of this journey with the community. I hope that the information presented here will be of great value to readers. I am currently very excited about this new phase of my career. I have learned a lot and would like to share some of this journey with the community. I hope that the information presented here will be of great value to readers. People First - The importance of Soft Skills When I participated in my first selection process, a few years ago, I clearly remember the almost boring steps I went through: interview with HR, practical test, interview with the technical leader and, finally, interview with the manager. Throughout my career as a developer, I have participated in several interviews with different models. At that time, I always felt uncomfortable interviewing with HR people. I didn’t quite understand why, thinking: “If I can do what is required in the technical test, I am already showing enough competence for the position.” When I took on my role as technical development leader, one of my responsibilities was to collaborate with HR (yes, the same people with whom I didn't understand the reason for participating in the selection process) in preparing a technical test and defining the interview format for two candidates starting in the backend area. I thought I already knew what a beginner developer in the backend area should deliver and what would be considered a differentiator in the test. However, what I didn't expect was that, despite the importance of the code, other demands arose beyond project delivery: how to evaluate candidates in terms of communication? What is their interest in the position? And how can the context they present influence their suitability for the proposed position? These and other questions turned out to be as relevant as the code presented by both candidates, something I had not previously considered in my early years as a developer. I remember sitting at the meeting table to make the final decision and being a little surprised to realize how little was discussed about each candidate's technical skills. Part of this was due to the fact that they were entry-level candidates, so it was to be expected that their technical skills would not be as developed, and this was not the main focus of the discussion. However, even for more advanced vacancies, especially for senior-level positions, it is crucial to consider skills such as communication, documentation, adaptability, proactivity and other skills often mentioned. These soft skills are fundamental and can be decisive for success in the role, in addition to technical skills. In fact, this is my next point. The line between Junior and Senior (No, not mid-level). I know there's a lot of discussion about the meaning and classification of terms related to experience levels, like "senior." Some say that "senior is defined by years of experience", others claim that "in some companies, you gain senior experience after a year". There are also those who say that "there is no clear distinction between junior and senior" or that "seniors only do code reviews and approve PRs". Some of these statements are comical, others have a grain of truth. The fact is that the concept of "senior" is quite varied and it is not up to me to define a universal standard, but I can offer some guidance to understand this classification in a more individual way. Being a senior is not just about technical knowledge, although this is undoubtedly very important. A true senior, or at least a good senior, is someone capable of solving complex problems in terms of both code and systems architecture. Maintaining code quality, following good development practices and having knowledge of project management are crucial aspects. Being a senior is not just about technical knowledge, although this is undoubtedly very important. A true senior, or at least a good senior, is someone capable of solving complex problems in terms of both code and systems architecture. Maintaining code quality, following good development practices and having knowledge of project management are crucial aspects. The key difference is that a senior must be able to execute all of this autonomously and, more importantly, collaborate with teams from different levels and sectors to deliver the best project possible. Furthermore, a real senior (or at least the best ones) not only leads and guides the team, but also develops and prepares other developers to take on new positions and responsibilities. My first experience leading a project When I took on my first project, my boss knew that I hadn't previously led any other project. I just participated in the development and worked out some things that would facilitate development in terms of communication with management. The first question he asked me was: "How many people and what kind of will be enough to complement the project." I didn't know the answer right away, it was a very complex question. Because the project was only in the outline, we had no idea of ​​the stack, how much time it would take to complete each task and other metrics of interest to the people above. I did a complete study to be able to deliver the next day on several project management methodologies: Pert, Planning Poker We collaboratively chose the one that was best suited and the challenge began. for each member of the team, what is the best development platform, what is the best stack to use, how the system architecture will work, studying other solutions on the market, monitoring the level of each developer, meetings, meetings and more meetings with the management . "How many people and what kind of will be enough to complement the project." meetings, meetings and more meetings with the management When I least realized it, I was increasingly distant from the code. My role became to suggest improvements and fix some critical bugs so that the project could work, or at least provide a solid foundation for the developers to start. The rest of the work involved communicating with the developers, dividing tasks, monitoring of metrics and, basically, one eye on Asana (to estimate project delivery time) and another on Meet to make sure my microphone wasn't on and nothing unwanted was "accidentally" slipped through. When I least realized it, I was increasingly distant from the code. My role became to suggest improvements and fix some critical bugs so that the project could work, or at least provide a solid foundation for the developers to start. Conclusion and a look at the past - to the master with affection I started my career as a development intern and, interestingly — and you might find it a little contradictory on my part — I didn't have any concrete experiences (at least not formally recorded in my employment record) that would classify me as a junior, full or senior developer. Much of the experience I gained came from personal projects and research at college. It was a gradual process until I realized that my skills had evolved since those early days. But yes, I worked intensely as a developer at different levels and had the opportunity to meet different types of senior professionals throughout my career: The very competent and effective senior, but uncommunicative, who solved problems without providing explanations about his approach. The senior is excellent at communication and teaching, but often overwhelmed with urgent tasks and no time to teach. The senior who was enthusiastic about over-engineering and centralizing technology, but who met deadlines and delivered what he promised. The very competent and effective senior, but uncommunicative, who solved problems without providing explanations about his approach. The senior is excellent at communication and teaching, but often overwhelmed with urgent tasks and no time to teach. The senior who was enthusiastic about over-engineering and centralizing technology, but who met deadlines and delivered what he promised. The most important thing is that, despite their justifiable flaws (although it is possible, it is very difficult to balance demands), all of these professionals had something valuable to teach. These experiences helped shape my career and gave me a clear view of what works and what doesn't in systems development.

The Surprising Lessons I've Learned as a Tech Lead

টেক লিড হিসেবে আমি যে আশ্চর্যজনক পাঠ শিখেছি

Die überraschenden Lektionen, die ich als technischer Leiter gelernt habe

Las sorprendentes lecciones que he aprendido como líder tecnológico

Les leçons surprenantes que j'ai apprises en tant que responsable technique

एक टेक लीड के रूप में मैंने जो आश्चर्यजनक सबक सीखे हैं

技術リーダーとして学んだ意外な教訓

기술 리더로서 내가 배운 놀라운 교훈

As lições surpreendentes que aprendi como líder de tecnologia

Удивительные уроки, которые я усвоил, работая техническим руководителем

Bir Teknoloji Lideri Olarak Öğrendiğim Şaşırtıcı Dersler

Những bài học đáng ngạc nhiên tôi đã học được với tư cách là Trưởng nhóm kỹ thuật

作为技术主管，我学到的令人惊讶的教训

My Testing Journey With Jasmine and Mocha: What I've Learned

JobQuest Assistant: How I Built a Smart Companion for Stress-Free Job Hunting With Coze

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JobQuest Assistant: Coze を使ってストレスフリーな就職活動のためのスマートなコンパニオンを構築する方法

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JobQuest Assistant: Coze로 스트레스 없는 취업 활동을 위한 스마트한 동반자를 만든 방법

JobQuest asistents: kā es izveidoju gudru kompanjonu darba meklējumiem bez stresa ar mājīgumu

JobQuest Yanapakuq: Imaynatataq huk Smart Compañerota ruwarqani Cozewan Mana Estrés Llamkana Cazapaq

JobQuest Assistant: Coze සමඟ ආතතියෙන් තොර රැකියා දඩයම් කිරීම සඳහා මම ස්මාර්ට් සහකාරියක් ගොඩනඟා ගත් ආකාරය

JobQuest kömekçisi: Coze bilen stresiz iş awlamak üçin akylly ýoldaş nädip gurdum

JobQuest Assistant: як я створив розумного компаньйона для пошуку роботи без стресу з Coze

Trợ lý JobQuest: Cách tôi xây dựng một người bạn đồng hành thông minh để tìm việc không căng thẳng với Coze

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