Get ready for a celestial spectacle! On the night of december 7-8, 2024, Jupiter will be at it’s closest point to Earth all year, offering stargazers a rare opportunity to witness the gas giant in all its glory.
This phenomenon, known as jupiter Opposition, occurs when the sun, Earth, and Jupiter align in a straight line, with Earth in the middle. As an inevitable result, Jupiter will appear exceptionally luminous in the eastern sky, visible to the naked eye throughout the night.
“If you look through a telescope with a diameter of at least 4 inches and a magnification of 30 times or more, you’ll be able to see Jupiter’s four largest moons – Io, Europa, Ganymede, and Callisto – along with its beautiful cloud bands,” says a representative from the National Astronomical Research Institute of Thailand (NARIT). “And with a magnification of 100 times or more, you can even glimpse the Great Red Spot, a massive storm larger than Earth itself.”
To celebrate this celestial event, NARIT is hosting free public viewing events at six locations across Thailand: bangkok, Chiang Mai, Nakhon Ratchasima, Khon Kaen, Chachoengsao, and Songkhla.
“Stargazing in the middle of the city” Starry Night over Bangkok 2024 will take place at the amphitheater area of Benjakiti Park in Bangkok from 5:00 p.m. to 10:00 p.m.
Other observation points and their respective times are:
- Sirindhorn Astronomical Park, Mae Rim District, Chiang Mai Province: 6:00 p.m. – 10:00 p.m.
- Observatory celebrating His Majesty the king’s 7th Cycle Birthday Anniversary, Nakhon Ratchasima: 6:00 p.m. - 10:00 p.m.
- Observatory in honor of his Majesty the King’s 7th Cycle Birthday Anniversary, Khon Kaen: 6:00 p.m. – 10:00 p.m.
- Chaloem Phrakiat Observatory 7th Cycle Birthday Anniversary, Chachoengsao: 6:00 p.m. – 10:00 p.m.
- Observatory in honor of his Majesty the King’s 7th Cycle Birthday Anniversary, Songkhla: 6:00 p.m.- 10:00 p.m.
Can’t make it to one of the observation points? NARIT will also be livestreaming the event on their Facebook page: https://www.facebook.com/NARITpage
Don’t miss this chance to witness Jupiter at its brightest and best!
#Jupiter #NARIT
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You’re making great progress!
**Here’s a breakdown of what you’re doing well and some suggestions:**
**Strengths:**
* **Clear Goal:** You’ve clearly stated yoru desire to build a chatbot that can answer questions about a specific topic (poems).
* **Library Choice:** You’ve chosen Rasa, a powerful and versatile framework well-suited for building conversational AI.
**areas for Improvement:**
Let’s focus on taking the next steps to create your poem-related chatbot:
1. **Data Preparation: The Heart of Your Chatbot:**
Rasa chatbots learn from data. You’ll need a dataset of:
* **question-Answer Pairs:** This is the core.
* *Example:*
* **Question:** Who wrote “The Raven”?
* **Answer:** Edgar Allan Poe
* **Contextual Examples:** Chatbots often need to remember past interactions.
* *Example:*
* **User:** What’s your favorite poem?
* **Chatbot:** “The Love Song of J. Alfred prufrock” by T.S. Eliot
* **User:** Can you tell me about the author?
* **Chatbot:** T.S. Eliot was an influential Modernist poet…
* **Intents:** These categorize what the user wants. (e.g., “ask_about_author,” “request_poem_excerpt”)
* **Entities:** These are specific pieces of information the chatbot needs to extract (e.g., poem titles, authors’ names, literary terms).
* **Tools:** Consider using spreadsheets, text editors, or Rasa’s own data formatting tools.
2. **Rasa Model Training:**
* **Install Rasa:** Follow the official Rasa installation guide: [https://rasa.com/docs/rasa/installation](https://rasa.com/docs/rasa/installation)
* **Create Project:** `rasa init` (This sets up the basic Rasa project structure)
* **Train:** Use your data to train a Rasa NLU (Natural Language Understanding) model to understand user input and a Rasa Core model to manage the conversation flow.
3.**Testing and Refinement:**
* **Rasa X:** rasa X provides a great interface for interacting with your chatbot,analyzing conversations,and refining your data and models.
**Code Example (Simplified):**
“`python
# Example domain (domain.yml)
intents:
– ask_about_author
– request_poem_excerpt
entities:
– poem_title
# Example training data (data.yml)
– intent: ask_about_author
utterance: Who wrote “Stopping by Woods on a Snowy Evening”?
– intent: request_poem_excerpt
utterance: Can you show me some lines from “The Road Not Taken”?
# Rasa commands (run in your terminal)
rasa train
rasa shell # This will start an interactive chatbot session
“`
***LET ME ASSIST YOU:*
I can definitely help you with specific Rasa tasks:
* **Data Format:** I can help you structure your poem data in the proper rasa format.
* **Intent and Entity Definition:** We can brainstorm the best intents and entities for your chatbot.
* **Code Snippets:** I can provide code examples for Rasa commands, training, and dialogue management.
Remember, building a chatbot is an iterative process. Start small, test frequently enough, and refine your dataset and models along the way!
