j1

[j1 @stockbaas]

@bryan_johnson What are your opinions on light glasses like ayo lite or luminette?

[j1 @stockbaas]

@MEnesKirca Quick

[j1 @stockbaas]

@damianplayer n8n

[j1 @stockbaas]

@heyabhishek @readwise save thread

[j1 @stockbaas]

@antinertia Arcads

[Rob Roos 🇳🇱 @Rob_Roos]

As citizens, we must reject #CBDC’s from day one.

There’s nothing wrong with our current payment systems—this is about control, not convenience.

Once they have you in their digital prison, every aspect of your life is at their mercy.

Stay free!

And share this message please.

[j1 @stockbaas]

@TaikiMaeda2 Didn’t age well

[j1 @stockbaas]

@Robin_ecomm AI

[j1 @stockbaas]

@0xULTI @CheetaWestern So what will happen now?

[MERIS 🦄💸 @merisknows]

@abu_crypto1 Check out @SquaresLabs ! Newly lauched token, simular to Vertical ai 😇 Mcap under 3 mill

[MoonKing @MoonKing___]

The launch of $OMIRA has been a great one so far

@OmiraAI actually reminded me of the golden fair launch days

The Omira-B.B4 model will soon go live at https://t.co/VL01xdvjfP

As soon as people try it out, the token will skyrocket ⌛

[Omira @OmiraAI]

Our focus to date has been to lay down the groundwork for our AI-powered price prediction model, B.B4. This process has included 4 major phases:

Research and planning, sentiment processing development, traditional price prediction development, and our integrated model development.

Our research and planning consisted of, for the most part, the solidification of our thesis that sentiment-integrated price predictions remain significantly more accurate than a traditional price prediction model. Once solidified, we began to lay down the necessary infrastructure (AWS for computational load, AWS S3 as a data lake solution) for storing and computing raw data to make Omira’s B.B4 a reality. We also importantly validated key data sources, ensuring a seamless integration with both third-party X-API sources, as well as the traditional X developer API.

In our second phase of development, sentiment processing, our goal was to build and solidify the core components that make B.B4 unique. Our data collection module was engineered to gather highly specific tweets and discussions from X, filtering through the noise via the identification of precise keyword and trend analysis. This is where BERT came into play (pre-processing with SpaCy, deep-learning with Hugging Face), where we fine-tuned our transformer-based NLP model to better understand and associate all crypto-related language and its nuances.

Our shift into the third phase of traditional price prediction development is where everything started to come together. Using a combination of LSTM models for time-series analyses, as well as ARIMA for long-term trends, we created a system that identifies and predicts patterns in trading volume and price action. With a focus on feature engineering (the strategic organization of data), we were able to efficiently inform our model and improve its accuracy.

In our current phase, the integrated model development, focuses on integrating our sentiment-related data with our baseline prediction model to create Omira-B.B4. Omira-B.B4 in its current stage is able to balance technical analysis with real-world emotional market drivers, notably the most influential aspect of low-cap price action.

We will soon be moving towards our Beta release of Omira-B.B4, allowing users to get a sense of what we’ve designed to-date, while contributing to the improvement of our models accuracy and usability.

[j1 @stockbaas]

@Remarks @WatcherGuru Bullish

[j1 @stockbaas]

@HouthakkerOpSok @AKaarten Heb je de kaart nog?

[Sawyer Merritt @SawyerMerritt]

Elon live

https://t.co/7pX33aaswv

[j1 @stockbaas]

@WatcherGuru LOL

[Thierry Baudet @thierrybaudet]

Ongelofelijk. #STEMZEWEG #FVD

[j1 @stockbaas]

@disclosetv 😴😴😴😴😴

[j1 @stockbaas]

@CcommissionerX @FelixTheCatEth Lets gooooooo!!!

[j1 @stockbaas]

@mr_pschmitt @FelixTheCatEth LFG 🥰