This episode is the second part of our two-part review of Ontology (this is a link to the first part).

It’s important to indicate that there’s no particular listening order associated with these two episodes.

Ontology is a decentralized platform, which was founded by Li Jun, who is also the co-founder of OnChain.

The platform comes with a set of protocols and modules - which are its building blocks.

Just as in LEGO kits, combining these various units does not require deep understanding of the very intricate internal workings of each one of them.

As we build higher levels in such way, there emerges a hierarchy which has a more holistic nature to it.

The associated behavior to this abstract structure comprises a complete set of features,

Despite the fact that the various notions and meanings of trust greatly rely on our very own self-preservation mechanisms, decentralized, open-source platforms, such as Ontology, enable

Our discussion touches upon a number of topics such as, but not limited to:

As usual, we look forward to your comments, ideas, suggestions and constructive criticism!

Enjoy! :)

N.B.: I was a bit sick during the recording of episode 6, and as a result, the voice quality is not exactly stellar. I believe this doesn’t interfere significantly with the presentation though.

This episode is the first part of a two-part review of the Ontology platform which was founded by Jun Li, who is also a co-founder of OnChain.

In this episode, we present an overview of the Ontology platform.

The listeners will get to learn what the unique characteristics of the project are and why its potential impact could literally affect our society, in its entirety, and change it for the better.

Our discussion touches upon a number of topics such as, but not limited to:

As usual, we look forward to your comments, ideas, suggestions and constructive criticism!

Enjoy! :)

In this tutorial-style episode, we’re going to go over the various steps that are required for setting up a ZenCash secure node. The discussion will be limited to a very high level, with the purpose of giving you a rough idea of the magnitude of the associated workload.

In a couple of sentences, ZenCash secure nodes enable reward entitlement for operators. Said nodes solve challenges, associated with computational validation of shielded transactions within the ZenCash blockchain. And this happens via a form of staking.

In this episode, intended to be a part of mini-series, we’re going to be reviewing some of the most common crypto-related scams, such as phishing, pumps-and-dumps and exit scams.

Scams and confidence tricks rely almost entirely on limitations and “blindspots” in human cognition and psychology, and those are exploited by malicious individuals or groups. That’s why I’ve decided to spend a significant portion of this episode on discussion these key aspects, because introspection, I believe, can be one of the most effective tools to equip oneself with, nowadays.

All security-related scenarios and contexts and characterized by asymmetry, where the attacking side usually needs to find just one single hole in the system in order to declare success, whereas the defending side needs to be able to cover the entire constellation of intersection points, which directly translate to attack vectors.

As saddened and disheartened all fair players can be at times, due to the ongoing high frequency of nefarious activities, we all need to take serious steps towards educating the wider crypto audience in any suitable opportunity.

That’s why I’ve opted to reshuffle my episode recording order a bit, and give priority to today’s topic.

In general, there’s really not that much to say in the form of side notes on 101-level scams. The episode content pretty much covers most important aspects I wanted to bring to your attention, in the context of the associated topics.

In addition to the audio content and accompanying notes, I’ve decided to create a section on my website, dedicated to keeping track of important scams to look out for, and having a sort of compilation in a single place, so that they can be referenced easily.

I invite you all to contribute with ideas and suggestions for keeping the repository as up-to-date and useful as possible. This can be done via the usual communication channels, namely our email or Discord server.

This is an introductory episode where the listeners will get a chance to learn about the host, his background and why he’s decided to finally start a new podcast.

Want to learn more about your favorite host, Crypto Jerônimo? About his vision of the blockchain future? His favorite recommended resources for beginners?

Well, look no further! This episode answers all of this and quite a bit more. Sit back, relax and enjoy! :)

… and not a “traditional” co-host? you ask. Well, I’ll tell you why.

Do you find this YouTube video surreal and Orwellian? I do. But not only that. I also value people’s time and believe that

Xora has enabled the production of very nice and conversational episodes just as well. Aside from the occasional firmware upgrade, I do not intend to replace her for a human replica :)

For an example script for TTS generation, please, refer to this code snippet. ↩

Crypto Jerônimo’s Musings was, in fact, born out of inspiration by Peter Ullrich’s amazing podcast, and its deep technical level of detail and academic flavor of delivery. ↩

This is an episode on the super cool Machine-Learning-powered hedge fund, Numerai.

Numerai is a global equity long-short hedge fund, which specializes in relatively long time-range investments, on the scale of 6-9 months. They’re interested in more finely granular moves, that are at the level of individual stocks; they aim to identify anomalously-priced stocks, and thus exploit price discrepancies. One might argue that their essential task is to restore market efficiency.

Collaboration in finance is largely uncommon and impractical due to the competitive edge that is characteristic to the kind of predictive modeling that is associated with the area. Numerai addresses this via running rounds of successive Machine Learning competitions for the purpose of crowdsourcing predictions, which then serve to form trading decisions on the traditional markets.

As of the time of recording this episode, Numeraire (NMR) was listed on the following exchanges:

The figures from the example, presented in the episode, were as follows:

The actual reward is calculated as R[i] = min(p[i], r), where i denotes the potential winnings of the ith participant (ranked in descending order of confidence); and r denotes the remaining prize pool amount.

The free electronic version of the book is, in fact, only available in HTML format, rather than PDF (the latter was originally indicated in the recording). ↩