Every problem that’s worth solving, has already been solved by nature. After millions of years, experimenting in milliards of species and a variety of environments, most likely, nature not only has found a solution for every problem but the best solution for each problem.
It’s been reported that over 90% of startups fail, half of those failures are attributed to a lack of customers. In parallel, our society has become prey to one of the most successful distribution strategies in history: COVID-19.
The term viral is often associated with marketing, but for the most part, we lack an understanding of…
I’m a founder, optimistic, and passionate, but jumping into a new business without understanding what is expected to happen after COVID-19 sounds delusional to me.
We love to think we are special, that our lives are unique, and what is happening to us is unprecedented, but guess what? So did people during the Middle Ages as they were crushed by the deadliest pandemic recorded in human history .
During the past two months, I’ve witnessed the meteoric rise in revenue of Copy.ai, a startup using Artificial Intelligence (GPT-3) for copywriting. I can only describe the experience with awe:
It led me to meditate about growth. In particular, how does growth happen in nature?
Most forces in nature, like tornados, and hurricanes, leave a trail of destruction behind them. But CopyAI is different it’s creating massive wealth: saving businesses thousands of hours, creating better marketing material than even humans could, and transforming the way we engage with information online.
It was up to me to understand what growth was…
Cybersecurity roles are expected to grow 750% in the next five years , now, if you are expecting that colleges, companies, and governments bridge the knowledge gap to fulfill those jobs, you’ve learned nothing from tech-history.
Those more than 5 million future jobs will be filled by high-driven individuals looking for a $99,730 yearly median-salary, in the US. 
But besides job stability and good earnings potential, there are plenty of good reasons to engage in a cyber-security related career:
On August 25th, Exxon was removed from the Dow Jones industrial index after 92 years in it . Exxon is one example of the innovator's dilemma, a company that once dominated its market and eventually was outpaced due to innovation. In particular, Exxon failed to adapt as its industry shifted towards renewable energies. And why wouldn’t they? Renewable energy was not going to give them the same thick margins as oil did, nor were they be willing to devalue their oil fields and massive investments in exploration. Yet, despite Exxon’s chunky margins, long tradition, and oligopoly control of the energy…
One image is worth a thousand words. Then, what if we could summarize a 1,000-word document in a single chart?
Charts and dashboards are used to model financial and numerical data. They are the preferred tool by analysts and investors to analyze, communicate, and strategize. But until a few years ago, using charts to visualize human language was not possible. Today, word embeddings make text documents faster to process, easier to aggregate, and more profitable to analyze.
Word embeddings are used in almost every commercial application that involves AI and human language. Some example applications include search engines, social media recommendation algorithms, language translation, speech recognition, market research, automated trading, and language generation.
Word embeddings are numerical representations of a word’s meaning. They are formed based on the assumption that meaning is contextual. That is, a word’s meaning is dependant on its neighbors:
Recent advances in Deep Learning have made it possible to extend the power of Artificial Intelligence into web browsers. Introduced in 2018, TensorflowJS enables web developers to integrate state-of-the-art models in their applications. One of these models, the universal-sentence-encoder, uses advances in Natural Language Processing to transform words and sentences into mathematical vectors known as word embeddings.
Developed by seminal papers in deep learning, including Google’s word2vec and Stanford’s GloVe. Word embedding unlocks a variety of applications: mapping synonyms and antonyms, deciphering analogies, measuring biases. A text recommendation engine can be understood as a similarity optimization problem. …
“Don’t be afraid to change the model.” — Reed Hastings
Consider a successful startup: let’s say AirBnB. As a novice, I would look at their website, their mobile app, and their business model (a marketplace), then come up with an “innovative” entrepreneurial idea and sell it as: “The AirBnB of <whatever industry sounds hot and interesting>.”
But if you actually watch the real history of AirBnB, you’ll notice they were more interested in:
I’m bewildered, I tended to look down upon sales as if it was lacking rigor, substance, or reproducibility. But I was wrong! Sales is a creative, disciplined effort to bring ideas to fruition.
Remember that first time you discovered the power behind Software Development? For me, it was in college, while studying Econometrics I stumbled on the Machine Learning course by Andrew Ng from Stanford. Suddenly, I realized I could do far superior data analysis using computer intelligent driven methods. I was at a dead-end.
After 10 years of developing software, the same doomed feeling arrived: unproductivity. Planning and designing…