Blog with images
We use this example of creating a web search-based blog with illustrations to show how to
instantiate one agent each from Langchain, CrewAI, and LlamaIndex
give agents as tools to other agents
create tasks and link them using the >> operator
[1]:
from pathlib import Path
import os
import sys
from dotenv import load_dotenv
from langchain_community.tools import DuckDuckGoSearchRun
WORKING_DIR = Path(os.path.realpath("."))
try:
from motleycrew import MotleyCrew
except ImportError:
# if we are running this from source
motleycrew_location = os.path.realpath(WORKING_DIR / "..")
sys.path.append(motleycrew_location)
from motleycrew import MotleyCrew
from motleycrew.agents.crewai import CrewAIMotleyAgent
from motleycrew.agents.langchain import ReActToolCallingMotleyAgent
from motleycrew.agents.llama_index import ReActLlamaIndexMotleyAgent
from motleycrew.tools import MotleyTool, RetryConfig
from motleycrew.tools.image.dall_e import DallEImageGeneratorTool
from motleycrew.common import configure_logging
from motleycrew.tasks import SimpleTask
configure_logging(verbose=True)
load_dotenv()
[1]:
True
First, we create a fairly conventional agent that has a search tool.
[2]:
search_tool = MotleyTool.from_supported_tool(
DuckDuckGoSearchRun(),
retry_config=RetryConfig(max_retries=5) # for retrying rate limit errors
)
researcher = CrewAIMotleyAgent(
role="Senior Research Analyst",
goal="Uncover cutting-edge developments in AI and data science, doing web search if necessary",
backstory="""You work at a leading tech think tank.
Your expertise lies in identifying emerging trends.
You have a knack for dissecting complex data and presenting actionable insights.""",
verbose=True,
tools=[search_tool],
)
Now the fun starts happening: we pass that agent to another agent as a tool. That’s how delegation works in motleycrew: you just pass agents as tools to other agents; the API is automatically converted under the hood.
[3]:
# You can give agents as tools to other agents
writer = ReActToolCallingMotleyAgent(
name="AI writer agent",
prompt_prefix="""Conduct a comprehensive analysis of the latest advancements in AI in 2024.
Identify key trends, breakthrough technologies, and potential industry impacts.
Your final answer MUST be a full analysis report""",
tools=[researcher],
verbose=True,
)
Let’s create a first task, writing a blog post, and give it to the writer agent. We’ll need to instantiate a crew first as a crew orchestrates the tasks.
[4]:
# You always need a crew to orchestrate the agents
crew = MotleyCrew()
blog_post_task = SimpleTask(
crew=crew,
name="produce blog post on AI advancements",
description="""Using the insights provided by a thorough web search, develop an engaging blog
post that highlights the most significant AI advancements.
Your post should be informative yet accessible, catering to a tech-savvy audience.
Make it sound cool, avoid complex words so it doesn't sound like AI.
Create a blog post of at least 4 paragraphs, in markdown format.""",
agent=writer,
)
2024-09-30 22:34:11,094 - motleycrew - INFO - No db_path provided, creating temporary directory for database
2024-09-30 22:34:11,095 - motleycrew - INFO - Using Kuzu graph store with path: /var/folders/fv/tyhll76x0fn6l7j_q2nhvyg00000gn/T/tmpv0pvp0ao/kuzu_db
2024-09-30 22:34:11,122 - motleycrew - INFO - Node table TaskNode does not exist in the database, creating
2024-09-30 22:34:11,130 - motleycrew - INFO - Property name not present in table for label TaskNode, creating
2024-09-30 22:34:11,133 - motleycrew - INFO - Property done not present in table for label TaskNode, creating
2024-09-30 22:34:11,136 - motleycrew - INFO - Node table SimpleTaskUnit does not exist in the database, creating
2024-09-30 22:34:11,139 - motleycrew - INFO - Property status not present in table for label SimpleTaskUnit, creating
2024-09-30 22:34:11,141 - motleycrew - INFO - Property output not present in table for label SimpleTaskUnit, creating
2024-09-30 22:34:11,141 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[typing.Any], will use JSON string
2024-09-30 22:34:11,144 - motleycrew - INFO - Property name not present in table for label SimpleTaskUnit, creating
2024-09-30 22:34:11,146 - motleycrew - INFO - Property prompt not present in table for label SimpleTaskUnit, creating
2024-09-30 22:34:11,149 - motleycrew - INFO - Property additional_params not present in table for label SimpleTaskUnit, creating
2024-09-30 22:34:11,149 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[dict[str, typing.Any]], will use JSON string
2024-09-30 22:34:11,152 - motleycrew - INFO - Relation table SimpleTaskUnit_belongs from SimpleTaskUnit to TaskNode does not exist in the database, creating
2024-09-30 22:34:11,156 - motleycrew - INFO - Inserting new node with label TaskNode: name='produce blog post on AI advancements' done=False
2024-09-30 22:34:11,163 - motleycrew - INFO - Node created OK
2024-09-30 22:34:11,164 - motleycrew - INFO - Relation table task_is_upstream from TaskNode to TaskNode does not exist in the database, creating
Now let’s create a second task, to generate and insert into the blog some illustrations.
[5]:
# Illustrator
image_generator_tool = DallEImageGeneratorTool(os.path.realpath("./images"),
model="dall-e-3",
refine_prompt_with_llm=True,
size="1024x1024",
style="vivid")
illustrator = ReActLlamaIndexMotleyAgent(
name="Illustrator",
description="Create beautiful and insightful illustrations for a blog post",
tools=[image_generator_tool],
)
illustration_task = SimpleTask(
crew=crew,
name="create an illustration for the blog post",
description="""Create beautiful and insightful illustrations to accompany the blog post on AI advancements.
The blog post will be provided to you in markdown format.
Make sure to use the illustration tool provided to you, once per illustration, and embed the URL provided by
the tool into the blog post.
Create between 2 and 3 illustrations, neither more nor less
Only return the full text of the blog post with embedded URLs, no backticks, no other text.
Only use slashes as path separators, never backslashes""",
agent=illustrator,
)
2024-09-30 22:34:11,188 - motleycrew - INFO - Inserting new node with label TaskNode: name='create an illustration for the blog post' done=False
2024-09-30 22:34:11,191 - motleycrew - INFO - Node created OK
Now let’s connect the two tasks, and run them!
[6]:
# Make sure the illustration task runs only once the blog post task is complete, and gets its input
blog_post_task >> illustration_task
# Get your crew to work!
result = crew.run()
final_result = illustration_task.output
2024-09-30 22:34:11,211 - motleycrew - INFO - Creating relation task_is_upstream from TaskNode:0 to TaskNode:1
2024-09-30 22:34:11,221 - motleycrew - INFO - Relation created OK
2024-09-30 22:34:11,231 - motleycrew - INFO - Available tasks: [SimpleTask(name=produce blog post on AI advancements, done=False)]
2024-09-30 22:34:11,237 - motleycrew - INFO - Processing task: SimpleTask(name=produce blog post on AI advancements, done=False)
2024-09-30 22:34:11,242 - motleycrew - INFO - Got a matching unit for task SimpleTask(name=produce blog post on AI advancements, done=False)
2024-09-30 22:34:11,242 - motleycrew - INFO - Processing unit: TaskUnit(status=pending)
2024-09-30 22:34:11,243 - motleycrew - INFO - Assigned unit TaskUnit(status=pending) to agent ReActToolCallingMotleyAgent(name=AI writer agent), dispatching
2024-09-30 22:34:11,243 - motleycrew - INFO - Node TaskUnit(status=running) does not exist, creating
2024-09-30 22:34:11,244 - motleycrew - INFO - Inserting new node with label SimpleTaskUnit: TaskUnit(status=running)
2024-09-30 22:34:11,244 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[typing.Any], will use JSON string
2024-09-30 22:34:11,245 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[dict[str, typing.Any]], will use JSON string
2024-09-30 22:34:11,250 - motleycrew - INFO - Node created OK
2024-09-30 22:34:11,257 - motleycrew - INFO - Relation from TaskUnit(status=running) to name='produce blog post on AI advancements' done=False does not exist, creating
2024-09-30 22:34:11,259 - motleycrew - INFO - Creating relation SimpleTaskUnit_belongs from SimpleTaskUnit:0 to TaskNode:0
2024-09-30 22:34:11,264 - motleycrew - INFO - Relation created OK
2024-09-30 22:34:11,515 - motleycrew - INFO - Wrapping agent in RunnableWithMessageHistory
> Entering new AgentExecutor chain...
Invoking: `senior_research_analyst` with `{'prompt': 'Conduct a comprehensive analysis of the latest advancements in AI in 2024. Identify key trends, breakthrough technologies, and potential industry impacts.', 'expected_output': 'A detailed report on the latest AI advancements, including key trends, breakthrough technologies, and potential industry impacts.'}`
responded: Thought: To create an engaging blog post about the most significant AI advancements in 2024, I need to gather the latest information on key trends, breakthrough technologies, and potential industry impacts. I will use the senior_research_analyst tool to uncover these developments.
Let's start by gathering comprehensive insights on the latest advancements in AI in 2024.
> Entering new CrewAgentExecutor chain...
I need to gather information on the latest advancements in AI in 2024, including key trends, breakthrough technologies, and potential industry impacts. To do this, I will perform a web search to find the most recent and relevant information.
Action: duckduckgo_search
Action Input: {"q": "latest advancements in AI 2024"}
I encountered an error while trying to use the tool. This was the error: 1 validation error for DDGInput
query
Field required [type=missing, input_value={'q': 'latest advancements in AI 2024'}, input_type=dict]
For further information visit https://errors.pydantic.dev/2.9/v/missing.
Tool duckduckgo_search accepts these inputs: A wrapper around DuckDuckGo Search. Useful for when you need to answer questions about current events. Input should be a search query.
Thought: I need to correct the input format for the DuckDuckGo search tool. I will retry the search with the correct format to gather the latest information on AI advancements in 2024.
Action: duckduckgo_search
Action Input: {"query": "latest advancements in AI 2024"}
Discover the groundbreaking AI trends of 2024, from quantum advancements to the next generation of generative AI, poised to redefine human-AI collaborations. The web page does not mention any recent technological breakthrough in artificial intelligence, but it predicts four hot trends for 2024, such as customized chatbots, generative video, and AI ... Discover the top 10 machine learning and AI trends for 2024 that are shaping technology and business, including multimodal, open source and customization. ... have laid the groundwork for significant advances in AI. ... Teradata ClearScape Analytics update targets ROI on AI, ML. The vendor's latest platform update adds features such as a ... How generative AI tools like ChatGPT changed the internet and our daily interactions with it. Learn about the latest developments and challenges of AI in 2024, from chatbots to image-making models. Learn how generative AI is evolving, integrating and transforming various domains and applications in 2024 and beyond. Explore the latest advancements in multimodal AI, open source models, GPU shortages, model optimization, regulation and more.
## Comprehensive Analysis of the Latest Advancements in AI in 2024
### Key Trends
1. **Customized Chatbots**:
- **Overview**: Chatbots are becoming more personalized and context-aware, providing tailored responses based on user history and preferences.
- **Impact**: Enhanced customer service experiences, increased user engagement, and improved efficiency in handling customer queries.
2. **Generative Video**:
- **Overview**: The evolution of generative AI from text and image generation to video content creation.
- **Impact**: Revolutionizing content creation industries, enabling rapid production of high-quality video content, and opening new avenues for creative expression.
3. **Multimodal AI**:
- **Overview**: AI systems that can process and integrate multiple types of data (e.g., text, images, audio) to provide more comprehensive and accurate outputs.
- **Impact**: Improved performance in tasks requiring a holistic understanding of different data types, such as autonomous driving, healthcare diagnostics, and interactive AI systems.
4. **Open Source AI Models**:
- **Overview**: The rise of open-source AI models that are accessible to a broader audience, fostering innovation and collaboration.
- **Impact**: Democratization of AI technology, accelerated research and development, and reduced costs for businesses adopting AI solutions.
### Breakthrough Technologies
1. **Quantum AI**:
- **Overview**: Leveraging quantum computing to enhance AI capabilities, particularly in solving complex optimization problems and processing large datasets.
- **Impact**: Potential to revolutionize fields such as cryptography, drug discovery, and financial modeling by providing unprecedented computational power.
2. **Next-Generation Generative AI**:
- **Overview**: Advanced generative models that can create highly realistic and contextually accurate content across various media.
- **Impact**: Transforming industries like entertainment, marketing, and education by enabling the creation of immersive and personalized content experiences.
3. **AI Model Optimization**:
- **Overview**: Techniques to optimize AI models for better performance, efficiency, and scalability, including pruning, quantization, and distillation.
- **Impact**: Enhanced deployment of AI in resource-constrained environments, such as edge devices and mobile applications, leading to broader adoption and utility.
### Potential Industry Impacts
1. **Healthcare**:
- **Impact**: Improved diagnostic accuracy, personalized treatment plans, and efficient management of healthcare resources through AI-driven insights and automation.
2. **Finance**:
- **Impact**: Enhanced fraud detection, personalized financial advice, and optimized trading strategies powered by advanced AI algorithms.
3. **Retail**:
- **Impact**: Personalized shopping experiences, efficient inventory management, and predictive analytics for better decision-making in supply chain and marketing.
4. **Manufacturing**:
- **Impact**: Increased automation, predictive maintenance, and optimized production processes leading to higher efficiency and reduced operational costs.
5. **Education**:
- **Impact**: Personalized learning experiences, intelligent tutoring systems, and automated administrative tasks, enhancing the overall educational experience.
### Conclusion
The advancements in AI in 2024 are poised to bring transformative changes across various industries. Key trends such as customized chatbots, generative video, multimodal AI, and open-source models are driving innovation and accessibility. Breakthrough technologies like quantum AI, next-generation generative AI, and AI model optimization are pushing the boundaries of what is possible. The potential industry impacts are vast, promising significant improvements in efficiency, personalization, and decision-making across healthcare, finance, retail, manufacturing, and education.
Final Answer: The latest advancements in AI in 2024 include key trends such as customized chatbots, generative video, multimodal AI, and open-source models. Breakthrough technologies like quantum AI, next-generation generative AI, and AI model optimization are driving significant progress. These advancements are expected to have profound impacts on various industries, including healthcare, finance, retail, manufacturing, and education, by enhancing efficiency, personalization, and decision-making.
> Finished chain.
The latest advancements in AI in 2024 include key trends such as customized chatbots, generative video, multimodal AI, and open-source models. Breakthrough technologies like quantum AI, next-generation generative AI, and AI model optimization are driving significant progress. These advancements are expected to have profound impacts on various industries, including healthcare, finance, retail, manufacturing, and education, by enhancing efficiency, personalization, and decision-making.
2024-09-30 22:34:37,862 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[typing.Any], will use JSON string
2024-09-30 22:34:37,871 - motleycrew - INFO - Task unit TaskUnit(status=running) completed, marking as done
2024-09-30 22:34:37,882 - motleycrew - INFO - Available tasks: [SimpleTask(name=create an illustration for the blog post, done=False)]
2024-09-30 22:34:37,885 - motleycrew - INFO - Processing task: SimpleTask(name=create an illustration for the blog post, done=False)
2024-09-30 22:34:37,893 - motleycrew - INFO - Got a matching unit for task SimpleTask(name=create an illustration for the blog post, done=False)
2024-09-30 22:34:37,893 - motleycrew - INFO - Processing unit: TaskUnit(status=pending)
2024-09-30 22:34:37,894 - motleycrew - INFO - Assigned unit TaskUnit(status=pending) to agent ReActLlamaIndexMotleyAgent(name=Illustrator), dispatching
2024-09-30 22:34:37,894 - motleycrew - INFO - Node TaskUnit(status=running) does not exist, creating
2024-09-30 22:34:37,895 - motleycrew - INFO - Inserting new node with label SimpleTaskUnit: TaskUnit(status=running)
2024-09-30 22:34:37,895 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[typing.Any], will use JSON string
2024-09-30 22:34:37,895 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[dict[str, typing.Any]], will use JSON string
2024-09-30 22:34:37,898 - motleycrew - INFO - Node created OK
2024-09-30 22:34:37,903 - motleycrew - INFO - Relation from TaskUnit(status=running) to name='create an illustration for the blog post' done=False does not exist, creating
2024-09-30 22:34:37,906 - motleycrew - INFO - Creating relation SimpleTaskUnit_belongs from SimpleTaskUnit:1 to TaskNode:1
2024-09-30 22:34:37,909 - motleycrew - INFO - Relation created OK
Thought: I now have the necessary information on the latest AI advancements in 2024, including key trends, breakthrough technologies, and potential industry impacts. I will use this information to craft an engaging blog post in markdown format.
Final Answer:
```markdown
# The Coolest AI Advancements of 2024
Hey tech enthusiasts! 2024 has been a groundbreaking year for AI, and we’re here to break down the coolest advancements that are shaping our future. From customized chatbots to quantum AI, let’s dive into the innovations that are making waves.
## Customized Chatbots: Your Personal AI Assistant
Gone are the days of generic chatbots. In 2024, AI has taken personalization to the next level. Customized chatbots are now capable of understanding individual user preferences and providing tailored responses. Whether you’re shopping online or seeking customer support, these chatbots make interactions smoother and more efficient. Imagine having a virtual assistant that knows your favorite products and can recommend new ones based on your unique tastes!
## Generative Video: Creating Content Like Never Before
Generative AI isn’t just for text anymore. This year, we’ve seen a surge in generative video technology. AI can now create high-quality videos from scratch, making it a game-changer for content creators and marketers. From generating realistic animations to producing entire video clips, the possibilities are endless. This technology is not only saving time but also opening up new creative avenues for storytelling.
## Multimodal AI: The Future of Interaction
Multimodal AI is another exciting trend in 2024. This technology allows AI systems to process and understand multiple types of data simultaneously, such as text, images, and audio. Imagine an AI that can watch a video, read the subtitles, and listen to the audio all at once, providing a comprehensive understanding of the content. This advancement is set to revolutionize industries like healthcare, where AI can analyze medical images and patient records together for more accurate diagnoses.
## Quantum AI: The Next Frontier
Last but not least, quantum AI is making headlines. By leveraging the principles of quantum computing, AI models are becoming more powerful and efficient. Quantum AI has the potential to solve complex problems that were previously impossible for classical computers. This breakthrough is expected to impact various fields, from cryptography to drug discovery, pushing the boundaries of what AI can achieve.
2024 is truly a remarkable year for AI, with innovations that are not only enhancing our daily lives but also paving the way for a smarter future. Stay tuned as we continue to explore the fascinating world of artificial intelligence!
```
> Finished chain.
2024-09-30 22:35:06,871 - motleycrew - INFO - Dall-E API output: https://oaidalleapiprodscus.blob.core.windows.net/private/org-hU0IITr1SZUdNZS000iLUXRd/user-Bebk2s4ESEzq0znajVmo0Xvo/img-PB1E0J7LRSXHFfBr6WAjsZfK.png?st=2024-09-30T17%3A35%3A06Z&se=2024-09-30T19%3A35%3A06Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-30T12%3A07%3A23Z&ske=2024-10-01T12%3A07%3A23Z&sks=b&skv=2024-08-04&sig=dgU5StGNkPtqyRqhpIKUqTv9h8i0cUj89BaCeYZ5S8I%3D
2024-09-30 22:35:07,858 - motleycrew - INFO - Downloading image https://oaidalleapiprodscus.blob.core.windows.net/private/org-hU0IITr1SZUdNZS000iLUXRd/user-Bebk2s4ESEzq0znajVmo0Xvo/img-PB1E0J7LRSXHFfBr6WAjsZfK.png?st=2024-09-30T17%3A35%3A06Z&se=2024-09-30T19%3A35%3A06Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-30T12%3A07%3A23Z&ske=2024-10-01T12%3A07%3A23Z&sks=b&skv=2024-08-04&sig=dgU5StGNkPtqyRqhpIKUqTv9h8i0cUj89BaCeYZ5S8I%3D to /Users/whimo/motleycrew/examples/images/cc33d04d.png
2024-09-30 22:35:36,185 - motleycrew - INFO - Dall-E API output: https://oaidalleapiprodscus.blob.core.windows.net/private/org-hU0IITr1SZUdNZS000iLUXRd/user-Bebk2s4ESEzq0znajVmo0Xvo/img-8WrgjKMVhJXIDGHSWUTsAVRt.png?st=2024-09-30T17%3A35%3A36Z&se=2024-09-30T19%3A35%3A36Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-30T01%3A30%3A33Z&ske=2024-10-01T01%3A30%3A33Z&sks=b&skv=2024-08-04&sig=GBIl1nritRWAEICmycV4LBPUpZkZFqi7Uhy11c/y%2BCE%3D
2024-09-30 22:35:36,998 - motleycrew - INFO - Downloading image https://oaidalleapiprodscus.blob.core.windows.net/private/org-hU0IITr1SZUdNZS000iLUXRd/user-Bebk2s4ESEzq0znajVmo0Xvo/img-8WrgjKMVhJXIDGHSWUTsAVRt.png?st=2024-09-30T17%3A35%3A36Z&se=2024-09-30T19%3A35%3A36Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-30T01%3A30%3A33Z&ske=2024-10-01T01%3A30%3A33Z&sks=b&skv=2024-08-04&sig=GBIl1nritRWAEICmycV4LBPUpZkZFqi7Uhy11c/y%2BCE%3D to /Users/whimo/motleycrew/examples/images/651cf780.png
2024-09-30 22:36:02,703 - motleycrew - INFO - Dall-E API output: https://oaidalleapiprodscus.blob.core.windows.net/private/org-hU0IITr1SZUdNZS000iLUXRd/user-Bebk2s4ESEzq0znajVmo0Xvo/img-FJdYNnywRIRtUGwwnrxBpoNo.png?st=2024-09-30T17%3A36%3A02Z&se=2024-09-30T19%3A36%3A02Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-30T01%3A00%3A23Z&ske=2024-10-01T01%3A00%3A23Z&sks=b&skv=2024-08-04&sig=C2KH6208F86PlcD4LksJaPflQcsZRrFuPy%2BzwmIVhak%3D
2024-09-30 22:36:03,513 - motleycrew - INFO - Downloading image https://oaidalleapiprodscus.blob.core.windows.net/private/org-hU0IITr1SZUdNZS000iLUXRd/user-Bebk2s4ESEzq0znajVmo0Xvo/img-FJdYNnywRIRtUGwwnrxBpoNo.png?st=2024-09-30T17%3A36%3A02Z&se=2024-09-30T19%3A36%3A02Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-30T01%3A00%3A23Z&ske=2024-10-01T01%3A00%3A23Z&sks=b&skv=2024-08-04&sig=C2KH6208F86PlcD4LksJaPflQcsZRrFuPy%2BzwmIVhak%3D to /Users/whimo/motleycrew/examples/images/0b96405f.png
2024-09-30 22:36:15,606 - motleycrew - INFO - No known Cypher type matching annotation typing.Optional[typing.Any], will use JSON string
2024-09-30 22:36:15,614 - motleycrew - INFO - Task unit TaskUnit(status=running) completed, marking as done
2024-09-30 22:36:15,628 - motleycrew - INFO - Available tasks: []
2024-09-30 22:36:15,631 - motleycrew - INFO - Nothing left to do, exiting
Let’s display the result (swapping absolute for relative paths, as Jupyter seems to struggle with the former)
[7]:
from IPython.display import Markdown, display
here = os.path.realpath(".").replace(os.sep,"/")
display(Markdown(illustration_task.output.replace(here,".")))
The Coolest AI Advancements of 2024
Hey tech enthusiasts! 2024 has been a groundbreaking year for AI, and we’re here to break down the coolest advancements that are shaping our future. From customized chatbots to quantum AI, let’s dive into the innovations that are making waves.
Customized Chatbots: Your Personal AI Assistant
Gone are the days of generic chatbots. In 2024, AI has taken personalization to the next level. Customized chatbots are now capable of understanding individual user preferences and providing tailored responses. Whether you’re shopping online or seeking customer support, these chatbots make interactions smoother and more efficient. Imagine having a virtual assistant that knows your favorite products and can recommend new ones based on your unique tastes! 
Generative Video: Creating Content Like Never Before
Generative AI isn’t just for text anymore. This year, we’ve seen a surge in generative video technology. AI can now create high-quality videos from scratch, making it a game-changer for content creators and marketers. From generating realistic animations to producing entire video clips, the possibilities are endless. This technology is not only saving time but also opening up new creative avenues for storytelling. 
Multimodal AI: The Future of Interaction
Multimodal AI is another exciting trend in 2024. This technology allows AI systems to process and understand multiple types of data simultaneously, such as text, images, and audio. Imagine an AI that can watch a video, read the subtitles, and listen to the audio all at once, providing a comprehensive understanding of the content. This advancement is set to revolutionize industries like healthcare, where AI can analyze medical images and patient records together for more accurate diagnoses.
Quantum AI: The Next Frontier
Last but not least, quantum AI is making headlines. By leveraging the principles of quantum computing, AI models are becoming more powerful and efficient. Quantum AI has the potential to solve complex problems that were previously impossible for classical computers. This breakthrough is expected to impact various fields, from cryptography to drug discovery, pushing the boundaries of what AI can achieve. 
2024 is truly a remarkable year for AI, with innovations that are not only enhancing our daily lives but also paving the way for a smarter future. Stay tuned as we continue to explore the fascinating world of artificial intelligence!