The A.I Megathread (LLM , GPT , Development)
Claude 3.5 Sonnet: HOW GOOD IS IT? - Claude101
Claude 3.5 Sonnet is a state-of-the-art large language model (LLM) developed by Anthropic. As the first release in the Claude 3.5 series.
claude101.com
Claude 3.5 Sonnet: HOW GOOD IS IT?
By Brady Hawkins 21 June 2024
What Is Claude 3.5 Sonnet?
Claude 3.5 Sonnet is a state-of-the-art large language model (LLM) developed by Anthropic. As the first release in the Claude 3.5 series.Claude 3.5 Sonnet builds upon the strengths of previous Claude models while introducing new capabilities that push the boundaries of what’s possible with AI language models. Its ability to grasp nuance, humor, and complex instructions makes it an invaluable tool for a variety of applications, from creative writing to technical problem-solving.
When Was Claude 3.5 Sonnet Launched?
Claude 3.5 Sonnet was officially launched on June 21, 2024. This release came as a surprise to many in the AI community, as Anthropic had not made any prior announcements about the development of a 3.5 version of their Claude model family.A brief Timeline of Claude Model releases:
- Claude 2 – Released in July 2023
- Claude 3 Family (Haiku, Sonnet, Opus) – Released in March 2024
- Claude 3.5 Sonnet – Released on June 20, 2024
The rapid succession of releases demonstrates Anthropic’s commitment to continuous improvement and innovation in the field of AI language models.
Where Can I Access Claude 3.5 Sonnet?
Claude 3.5 Sonnet is accessible through multiple platforms, making it easy for users to engage with the model based on their preferences and needs.Here are the primary ways to access Claude 3.5 Sonnet:
- Claude.ai Website: The official Claude website (Claude) offers free access to Claude 3.5 Sonnet.
- Claude iOS App: For users on the go, the Claude iOS app provides mobile access to Claude 3.5 Sonnet. This allows for seamless interaction with the model from iPhones and iPads.
- Anthropic API: Developers and businesses can integrate Claude 3.5 Sonnet into their applications and services using the Anthropic API. This option provides more flexibility and control over how the model is used.
- Amazon Bedrock: Claude 3.5 Sonnet is available through Amazon’s Bedrock service, which offers a managed platform for deploying and scaling AI models.
- Google Cloud’s Vertex AI: Users of Google Cloud can access Claude 3.5 Sonnet through the Vertex AI platform, enabling integration with other Google Cloud services.
- Some other third-party AI like tools (like Perplexity, Poe, etc.) with Claude 3 integration will like offer Claude 3.5 Sonnet too.
Is Claude 3.5 Sonnet Available for Free?
Yes, Claude 3.5 Sonnet is available for free through the Claude.ai website and iOS app. Keep in mind that free usage may have certain limitations compared to paid plans.Free vs. Paid Access:
- Free Access: Available on Claude.ai and the iOS app, with potential usage limits
- Claude Pro: Subscription plan offering higher rate limits and additional features
- Claude Team: Enterprise-level plan for organizations requiring extensive usage and support
Can I Access Claude 3.5 Sonnet Via API?
Yes. For developers and businesses looking to integrate Claude 3.5 Sonnet into their applications or services, Anthropic provides API access through:- Anthropic API: Anthropic offers a dedicated API for developers to access and leverage Claude 3.5 Sonnet’s capabilities programmatically.
- Amazon Bedrock: Claude 3.5 Sonnet is available on Amazon’s Bedrock platform, enabling seamless integration with AWS services and applications.
- Google Cloud’s Vertex AI: Google Cloud users can access Claude 3.5 Sonnet through the Vertex AI platform, facilitating AI model deployment and management.
You can review Anthropic’s API documentation for detailed information on available endpoints, request parameters, and best practices for using the API effectively.
How Much Does Claude 3.5 Sonnet Cost Per Million Input & Output Tokens?
Claude 3.5 Sonnet operates on a token-based pricing model, with separate costs for input and output tokens. Here’s a breakdown of the pricing:- Input Tokens: $3 per million tokens
- Output Tokens: $15 per million tokens
To put this into perspective, let’s consider an example:Scenario: You’re using Claude 3.5 Sonnet to generate a 1000-word article based on a 200-word prompt.Approximate token count:
- Input (prompt): 200 words ≈ 267 tokens
- Output (generated article): 1000 words ≈ 1333 tokens
Cost calculation:
- Input cost: (267 / 1,000,000) * $3 = $0.000801
- Output cost: (1333 / 1,000,000) * $15 = $0.019995
- Total cost: $0.000801 + $0.019995 = $0.020796
In this scenario, generating a 1000-word article would cost approximately 2 cents. These costs are significantly lower than those of Claude 3 Opus, which was priced at $15 per million input tokens and $75 per million output tokens. This pricing structure makes Claude 3.5 Sonnet a more cost-effective option for many use cases, especially those requiring frequent or large-scale interactions with the model.
What Is the Token Context Window Length for Claude 3.5 Sonnet?
The token context window is a critical feature of any language model, determining how much information it can process and retain during a single interaction. For Claude 3.5 Sonnet, Anthropic has maintained the impressive context window introduced with the Claude 3 family: 200,000 tokens.To put the 200,000 token context window into perspective, it’s equivalent to approximately 150,000 words or 300 pages of text.
The extensive context window of Claude 3.5 Sonnet sets it apart from many other language models, making it particularly well-suited for tasks that require processing and understanding large amounts of information.
How Does Claude 3.5 Sonnet Compare to Claude 3 Opus?
Claude 3.5 Sonnet represents a significant advancement over its predecessor, Claude 3 Opus, in several areas.Here’s a detailed comparison of the two models:
- Intelligence and Reasoning
Claude 3.5 Sonnet outperforms Claude 3 Opus across a wide range of evaluations, including:
- Graduate-level reasoning (GPQA)
- Undergraduate-level knowledge (MMLU)
- Coding proficiency (HumanEval)
- Processing Speed
Claude 3.5 Sonnet operates at twice the speed of Claude 3 Opus, making it more efficient for tasks requiring rapid responses or processing large amounts of data.
- Cost-Effectiveness
Claude 3.5 Sonnet is significantly more cost-effective than Claude 3 Opus:
- Claude 3.5 Sonnet: $3 per million input tokens, $15 per million output tokens
- Claude 3 Opus: $15 per million input tokens, $75 per million output tokens
- Natural Language Understanding
Claude 3.5 Sonnet shows marked improvements in:
- Grasping nuance and humor
- Understanding and following complex instructions
- Generating high-quality content with a natural, relatable tone
- Vision Capabilities
Claude 3.5 Sonnet surpasses Claude 3 Opus on standard vision benchmarks, particularly excelling in tasks requiring visual reasoning.
Claude 3.5 Sonnet’s benchmark results, comparing to other popular models
Here’s a comparison table between the two:
| Feature | Claude 3.5 Sonnet | Claude 3 Opus |
|---|---|---|
| Intelligence | Higher performance across benchmarks | Previously top-performing model |
| Processing Speed | 2x faster | Baseline speed |
| Input Token Cost | $3 per million | $15 per million |
| Output Token Cost | $15 per million | $75 per million |
| Coding Problem Solving | 64% success rate | 38% success rate |
| Vision Capabilities | Improved performance | Strong, but outperformed by 3.5 Sonnet |
| Context Window | 200,000 tokens | 200,000 tokens |
What Are the Vision Capabilities of Claude 3.5 Sonnet?
One of the standout features of Claude 3.5 Sonnet is its exceptional vision capabilities, surpassing even Claude 3 Opus on standard vision benchmarks. These advancements are particularly noticeable in tasks that require visual reasoning, such as interpreting charts, graphs, and other complex visual data.
Here’s a detailed breakdown of the Visual Understanding abilities of Claude 3.5 Sonnet:
- Visual Reasoning: Claude 3.5 Sonnet excels at tasks requiring interpreting and analyzing visual data, such as:
- Understanding complex charts, graphs, and diagrams
- Analyzing infographics and scientific visualizations
- Interpreting spatial relationships and context within scenes
- Understanding complex charts, graphs, and diagrams
- Image-Text Integration: The model can seamlessly integrate information from images and text, enabling comprehensive understanding and analysis.
- Object Recognition: Claude 3.5 Sonnet can accurately identify and describe objects within images.
- Visual Question Answering: Users can ask questions about images, and the model provides detailed, accurate responses based on visual analysis.
- Image-Based Problem-Solving: Claude 3.5 Sonnet can leverage visual information to assist in problem-solving tasks, such as analyzing architectural plans or engineering diagrams.
- Artistic and Design Analysis: The model can provide insights on artistic styles, design elements, and visual aesthetics.
- Handwriting Recognition: The model demonstrates improved capabilities in recognizing and transcribing handwritten text.
- Visual Data Extraction: Claude 3.5 Sonnet can extract relevant information from visually presented data, such as tables or charts embedded in images.
Can Claude 3.5 Sonnet Transcribe Text From Images?
Yes, Claude 3.5 Sonnet has the remarkable ability to transcribe text from images accurately, even when dealing with imperfect or low-quality images.Here’s another breakdown of the Text Transcription Capabilities of Claude 3 Sonnet:
- Handling Imperfect Images: Claude 3.5 Sonnet can transcribe text from images that are not perfect, including:
- Slightly blurry or out-of-focus images
- Images with poor lighting conditions
- Scanned documents with some distortion
- Slightly blurry or out-of-focus images
- Multiple Text Styles: The model can handle various text styles, such as:
- Printed text in different fonts
- Handwritten text (with varying degrees of legibility)
- Stylized text (e.g., logos, artistic typography)
- Printed text in different fonts
- Multiple Languages: Claude 3.5 Sonnet can transcribe text in multiple languages, making it useful for international or multilingual documents.
- Context Understanding: The model doesn’t just transcribe text; it can also understand the context of the text within the image, aiding interpretation and analysis.
- Formatting Retention: When transcribing structured text (like tables or forms), Claude 3.5 Sonnet can often retain or describe the original formatting.
What Is the Claude 3.5 Model Family?
The Claude 3.5 model family is Anthropic’s latest generation of AI models, designed to push the boundaries of intelligence, speed, and cost-effectiveness. While Claude 3.5 Sonnet is the first release in this series, Anthropic has plans to introduce additional models to cater to diverse use cases and requirements.Upcoming Models in the Claude 3.5 Family
Anthropic has announced that it will be releasing two additional models in the Claude 3.5 family later this year:- Claude 3.5 Haiku: A lightweight model designed for quick summary tasks and rapid responses, catering to scenarios where speed is of the utmost importance.
- Claude 3.5 Opus: The flagship model in the Claude 3.5 series, promising even greater intelligence and capabilities than Claude 3.5 Sonnet, albeit at a higher computational cost.
With the introduction of these models, users and organizations will have access to a comprehensive suite of AI solutions.
When Will Claude 3.5 Haiku and Claude 3.5 Opus Be Released?
Anthropic has not provided specific release dates for Claude 3.5 Haiku and Claude 3.5 Opus. However, the company has stated that both models will be released later in 2024.In the announcement for Claude 3.5 Sonnet, Anthropic mentioned:”To complete the Claude 3.5 model family, we’ll be releasing Claude 3.5 Haiku and Claude 3.5 Opus later this year.”
Although no exact timeline was given, it is expected that Anthropic will continue its rapid pace of innovation and release the remaining models within the next few months, potentially before the end of 2024.
OpenAI says GPT-5 will have 'Ph.D.-level' intelligence | Digital Trends
In a new interview, OpenAI CTO Mira Murati describes how intelligent the next generation of AI will be, and when we can expect it.
www.digitaltrends.com
GPT-5 will have ‘Ph.D.-level’ intelligence
By Luke Larsen June 20, 2024 4:46PM
The next major evolution of ChatGPT has been rumored for a long time. GPT-5, or whatever it will be called, has been talked about vaguely many times over the past year, but yesterday, OpenAI Chief Technology Officer Mira Murati gave some additional clarity on its capabilities.
In an interview with Dartmouth Engineering that was posted on X (formerly Twitter), Murati describes the jump from GPT-4 to GPT-5 as someone growing from a high-schooler up to university.
“If you look at the trajectory of improvement, systems like GPT-3 were maybe toddler-level intelligence,” Murati says. “And then systems like GPT-4 are more like smart high-schooler intelligence. And then, in the next couple of years, we’re looking at Ph.D. intelligence for specific tasks. Things are changing and improving pretty rapidly.”
Interestingly, the interviewer asked her to specify the timetable, asking if it’d come in the next year. Murati nods her head, and then clarifies that it’d be in a year and a half. If that’s true, GPT-5 may not come out until late 2025 or early 2026. Some will be disappointed to hear that the next big step is that far away.
After all, the first rumors about the launch time of GPT-5 were that it would be in late 2023. And then, when that didn’t turn out, reports indicated that it would launch later this summer. That turned out to be GPT-4o, which was an impressive release, but it wasn’t the kind of step function in intelligence Murati is referencing here.
In terms of the claim about intelligence, it confirms what has been said about GPT-5 in the past. Microsoft CTO Kevin Scott claims that the next-gen AI systems will be “capable of passing Ph.D. exams” thanks to better memory and reasoning operations.
Murati admits that the “Ph.D.-level” intelligence only applies to some tasks. “These systems are already human-level in specific tasks, and, of course, in a lot of tasks, they’re not,” she says.
1/1
Mira Murati: GPT-3 was toddler-level, GPT-4 was a smart high schooler and the next gen, to be released in a year and a half, will be PhD-level
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Mira Murati: GPT-3 was toddler-level, GPT-4 was a smart high schooler and the next gen, to be released in a year and a half, will be PhD-level
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1/1
i showed a fully local, computer-controlling AI a sticky note with my wifi password. it got online.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
i showed a fully local, computer-controlling AI a sticky note with my wifi password. it got online.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
Dolphin 2.9.1 Qwen 110B By cognitivecomputations: Benchmarks and Detailed Analysis. Insights on Dolphin 2.9.1 Qwen 110B.
LLM Card: 110b LLM, VRAM: 193.4GB, Context: 32K, License: other.
llm.extractum.io
1/1
I am currently testing the performance of GPT-4.0 and Claude 3.5 for coding tasks. It appears that Claude responds better, even with a brief prompt, but it’s too early to draw conclusions. I will have more insights soon.
Prompt
Design an interface for a blog using HTML and CSS.
GPT
Claude
@OpenAI
@AnthropicAI
#aifight #openai #claude #claudeai #html #cssource #css #html2024 #anthropicai
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
I am currently testing the performance of GPT-4.0 and Claude 3.5 for coding tasks. It appears that Claude responds better, even with a brief prompt, but it’s too early to draw conclusions. I will have more insights soon.
Prompt
Design an interface for a blog using HTML and CSS.
GPT
Claude
@OpenAI
@AnthropicAI
#aifight #openai #claude #claudeai #html #cssource #css #html2024 #anthropicai
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/1
These are all made with Claude 3.5 Sonnet.
For.
The LawFirmCRM Webpage - I gave it a database schema to create a page based on it.
JobHub - I told it to create an indeed styles job board.
E-learning - I told it to recreate a page based on a screenshot.
AI is actually good at designing UX/UI, now.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
These are all made with Claude 3.5 Sonnet.
For.
The LawFirmCRM Webpage - I gave it a database schema to create a page based on it.
JobHub - I told it to create an indeed styles job board.
E-learning - I told it to recreate a page based on a screenshot.
AI is actually good at designing UX/UI, now.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/6
To start, if you want to see Claude 3.5 Sonnet in action solving a simple pull request, here's a quick demo video we made.
(voiceover by the one and only @sumbhavsethia)
2/6
In our internal pull request eval, Claude 3.5 Sonnet passed 64% of our test cases.
To put this in comparison, Claude 3 Opus only passed 38%.
3/6
3.5 Sonnet performed so well that it almost felt like it was playing with us on some of the test cases.
It would find the bug, fix it, and spend the rest of its output tokens going back and updating the repo documentation and code comments.
4/6
Side note: With Claude's coding skills plus Artifacts, I've already stopped using most simple chart, diagram, and visualization software.
I made the chart above in just 2 messages.
5/6
Back to PRs, Claude 3.5 Sonnet is the first model I've seen change the timelines of some of the best engineers I know.
This is a real quote from one of our engineers after Claude 3.5 Sonnet fixed a bug in an open source library they were using.
6/6
At Anthropic, everyone from non-technical people with no coding experience to tenured SWEs now use Claude to write code that saves them hours of time.
Claude makes you feel like you have superpowers, suddenly no problem is too ambitious.
The future of programming is here folks.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
To start, if you want to see Claude 3.5 Sonnet in action solving a simple pull request, here's a quick demo video we made.
(voiceover by the one and only @sumbhavsethia)
2/6
In our internal pull request eval, Claude 3.5 Sonnet passed 64% of our test cases.
To put this in comparison, Claude 3 Opus only passed 38%.
3/6
3.5 Sonnet performed so well that it almost felt like it was playing with us on some of the test cases.
It would find the bug, fix it, and spend the rest of its output tokens going back and updating the repo documentation and code comments.
4/6
Side note: With Claude's coding skills plus Artifacts, I've already stopped using most simple chart, diagram, and visualization software.
I made the chart above in just 2 messages.
5/6
Back to PRs, Claude 3.5 Sonnet is the first model I've seen change the timelines of some of the best engineers I know.
This is a real quote from one of our engineers after Claude 3.5 Sonnet fixed a bug in an open source library they were using.
6/6
At Anthropic, everyone from non-technical people with no coding experience to tenured SWEs now use Claude to write code that saves them hours of time.
Claude makes you feel like you have superpowers, suddenly no problem is too ambitious.
The future of programming is here folks.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
Last edited:
1/1
It's been quite the year
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
It's been quite the year
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/1
Wow! claude-3.5 is an extremely impressive overall model! It achieves the top score in **every category**, and substantially improves in reasoning! See for yourself with our interactive leaderboard: LiveBench
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
Wow! claude-3.5 is an extremely impressive overall model! It achieves the top score in **every category**, and substantially improves in reasoning! See for yourself with our interactive leaderboard: LiveBench
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/1
It's been quite the year
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
It's been quite the year
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/1
Claude Sonnet just solved an engineering problem I’ve been fussing with for months in under 2 hours. A self-improving, self-terminating one-file-setup coding algorithm. You can have it. Here it is: NovaSystem/freebies/auto-coder at main · ctavolazzi/NovaSystem
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
Claude Sonnet just solved an engineering problem I’ve been fussing with for months in under 2 hours. A self-improving, self-terminating one-file-setup coding algorithm. You can have it. Here it is: NovaSystem/freebies/auto-coder at main · ctavolazzi/NovaSystem
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/11
I'm speechless. The new Anthropic model, Claude Sonnet 3.5 is the greatest model in reasoning capabilities.
Here’s my initial experiment:
Setup and Context
First, I uploaded a complex chat showing the prices of:
- US Dollar
- S&P 500 Index
- Bank interest rate
I added this system prompt:
"You are an expert developer and trader with godlike reasoning capabilities as well as profound technical knowledge. Do whatever user asks for and never stop with the expected output; always try to satify the user by providing more insights, analysis or even breakthroughs."
To enhance the output, I provided additional information:
"Consider the following events:
1. Mild recession beginning in 2022, coinciding with rate hikes
2. Recent rate cuts by:
Bank of Canada
Swiss National Bank
3. Rumored upcoming rate cut by: Bank of England
4. Cautious expectations regarding rate cuts by: Federal Reserve (US)"
Initial Tasks and Analysis
I first asked the model to write the index prices into a JSON file.
It extracted the information from the image and created the file accurately.
This initial step already showcased its impressive ability to handle complex tasks involving both vision and data extraction.
It's something that many models struggle with, yet Claude Sonnet 3.5 did it seamlessly, demonstrating its advanced capabilities.
Next, I asked for a detailed correlation analysis and trading strategies: "Impressive. Now I want you to deep dive into the correlations and future predictions. Write a very detailed analysis. Think like the best trader, best hacker, best creative..."
The model goes beyond basic correlations and predictions. It provides context, acknowledges exceptions, and offers a nuanced understanding of complex relationships.
Also, it doesn’t just stop at identifying correlations; the model explains why those relationships exist and under what conditions they might change.
This is particularly useful for traders and analysts who need to understand not just the "what" but also the "why" behind market movements.
Instead of offering a single prediction, the model considers multiple scenarios and their potential impacts.
This is critical for financial analysis, where outcomes are rarely certain, and preparing for various possibilities can be the key to successful trading and investment strategies.
Let's first see how it analyzed the correlations:
---
Correlation Analysis:
a) Federal Funds Rate and U.S. Dollar Index:
There's a generally positive correlation between these two variables. When interest rates rise, the dollar tends to strengthen. This is evident in the period from 2022 to early 2024, where both the Federal Funds Rate and the Dollar Index increased significantly. However, this correlation isn't perfect, as seen in the 2015-2018 period where the dollar weakened despite rising rates.
b) Federal Funds Rate and S&P 500:
The relationship here is more complex. Historically, moderate rate hikes often coincided with bull markets (e.g., 2016-2018). However, rapid rate increases, like those seen in 2022, can lead to market corrections. Interestingly, the S&P 500 has shown remarkable resilience, reaching new highs despite high interest rates in 2023-2024.
c) U.S. Dollar Index and S&P 500:
These two often move inversely, as a stronger dollar can hurt multinational companies' overseas earnings. However, in recent years (2020-2024), we've seen periods where both have risen simultaneously, suggesting other factors (like global economic recovery and tech sector growth) are influencing the S&P 500.
---
The model correctly identifies a general positive correlation between interest rates and the dollar index. This is a well-known relationship because higher interest rates typically attract foreign investment, boosting the dollar.
It mentions periods where this correlation didn’t hold, such as 2015-2018. This kind of insight is invaluable because it warns users that correlations are not absolute and can be influenced by other factors.
Let's continue with the predictions of the model:
---
Future Predictions:
a) Interest Rates:
Given the recent cautious stance of the Federal Reserve, I predict a gradual easing of rates starting in late 2024 or early 2025. The Fed will likely want to see sustained evidence of inflation cooling before making significant cuts. Expect 2-3 rate cuts of 25 basis points each in 2024, bringing the Federal Funds Rate to around 4.75-5% by year-end.
b) U.S. Dollar Index:
As other central banks (Bank of Canada, Swiss National Bank) have already started cutting rates, the dollar may maintain its strength in the short term. However, as the Fed eventually joins the rate-cutting cycle, we could see the Dollar Index retreat to the 98-100 range by end of 2024.
c) S&P 500:
The index has shown remarkable resilience. Given the potential for rate cuts and continued AI-driven tech growth, I predict the S&P 500 could reach 5300-5500 by end of 2024. However, this is contingent on a "soft landing" scenario where inflation is controlled without triggering a severe recession.
---
The model explains that moderate rate hikes can coincide with bull markets, while rapid increases can lead to corrections.
This reflects a sophisticated understanding of how interest rates can impact equity markets differently depending on the rate of change and the broader economic context.
Noting the resilience of the S&P 500 despite high rates in 2023-2024 is an important observation, indicating that other factors, such as technological advancements, might be at play.
While these typically move inversely, the model highlights periods when both rose simultaneously, suggesting other influences like global recovery and tech sector growth.
This is a great example of the model's ability to provide context-specific insights.
I can't wait to feed Anthropic Sonnet 3.5 over the upcoming months, but I can clearly say that you can't get this kind of technical reasoning and valid predictions from GPT-4 or other models. I also really liked the language and tone of the model.
But you know what, it hasn't even started yet.
In the same output, it also provided potential black swan events and algorithmic trade opportunities (I had to use a larger token size because it got cut in half).
But let's check the trading strategy suggestions;
---
Trading Strategies:
a) Yield Curve Trading: With potential rate cuts on the horizon, consider a "steepener" trade, betting on the yield curve steepening as short-term rates fall faster than long-term rates.
b) Sector Rotation: As rates potentially decrease, rotate into sectors that benefit from lower rates, such as Real Estate and Utilities. However, maintain exposure to tech stocks that have shown resilience in various rate environments.
c) Dollar-Sensitive Plays: If the dollar weakens as predicted, look into multinational companies with significant overseas revenue, as well as emerging market ETFs that could benefit from a weaker dollar.
d) Options Strategies: Consider long-dated call options on the S&P 500 to benefit from potential upside while limiting downside risk. Alternatively, use a collar strategy to protect gains while still participating in potential upside.
Potential Black Swan Events:
a) Geopolitical Tensions: Escalation of conflicts in Ukraine or the Middle East could lead to safe-haven flows, strengthening the dollar and potentially causing market volatility.
b) Tech Bubble Burst: The concentration of S&P 500 gains in a few large tech stocks poses a risk. Any significant regulatory action or earnings disappointment could trigger a broader market selloff.
c) Inflation Resurgence: If inflation proves stickier than expected, the Fed might be forced to maintain high rates for longer, potentially triggering a more severe recession.
Algorithmic Trading Opportunities:
a) High-Frequency Trading: Develop algorithms to capitalize on short-term discrepancies between interest rate expectations and currency movements.
b) Machine Learning Models: Train models on historical data to predict S&P 500 movements...
---
Predicting a gradual easing of rates aligns well with current economic conditions and the cautious stance of the Federal Reserve.
This kind of prediction is useful for planning long-term investment strategies.
The detailed forecast of 2-3 rate cuts bringing rates to 4.75-5% by year-end 2024 is precise and actionable, helping investors set expectations and plan accordingly.
The model's prediction of short-term dollar strength followed by a retreat as the Fed cuts rates is logical and reflects an understanding of global monetary policy dynamics.
Providing a specific range (98-100) adds clarity and helps in setting more precise trading strategies.
The prediction of the S&P 500 reaching 5300-5500 is optimistic yet grounded in current trends like AI-driven tech growth. It’s contingent on a “soft landing” scenario, which is a realistic assessment.
Mentioning the conditions (controlled inflation and avoiding a severe recession) shows that the model’s predictions are not just hopeful but based on realistic scenarios.
Yield Curve Trading:
Sophisticated Strategy: Suggesting a steepener trade reflects an advanced understanding of bond markets. This strategy is timely given the potential rate cuts.
Sector Rotation:
Actionable Advice: Rotating into sectors that benefit from lower rates while maintaining tech exposure is a balanced approach, showing the model’s ability to think strategically about portfolio management.
Dollar-Sensitive Plays:
Global Perspective: This strategy leverages the model’s earlier analysis of the dollar index and provides actionable insights for global exposure.
Options Strategies:
Risk Management: The inclusion of options strategies like long-dated call options and collar strategies demonstrates a sophisticated approach to risk management and leveraging opportunities.
Black Swan Events:
Geopolitical Tensions, Tech Bubble Burst, Inflation Resurgence: Identifying these potential black swan events shows the model’s depth of risk analysis, considering various factors that could disrupt markets. This helps traders and investors prepare for unexpected scenarios.
It even touched upon potential Nvidia crashes or AI regulatory affects on the market.
This is just a quick overview of the model, but it's super impressive!
Smarter, faster, cheaper.
Great job @AnthropicAI @alexalbert__
2/11
Great stuff, very impressive results.
3/11
Thank you, Andrew. Super exciting!
4/11
Great tutorial. When you uploaded the data did you add multiple years or just some shorter duration? Simple excel file or some other way.
5/11
I just uploaded this image and asked it to write the prices into a JSON file.
6/11
Great work!
7/11
Thank you
8/11
The S&P is already approaching 5500. When did you write this?
9/11
This is the chart that I used. Probably around Feb March
10/11
Absolutely amazing, thanks for sharing! @didier_lopes FYI
11/11
Thank you. Great opportunity for OpenBB!
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
I'm speechless. The new Anthropic model, Claude Sonnet 3.5 is the greatest model in reasoning capabilities.
Here’s my initial experiment:
Setup and Context
First, I uploaded a complex chat showing the prices of:
- US Dollar
- S&P 500 Index
- Bank interest rate
I added this system prompt:
"You are an expert developer and trader with godlike reasoning capabilities as well as profound technical knowledge. Do whatever user asks for and never stop with the expected output; always try to satify the user by providing more insights, analysis or even breakthroughs."
To enhance the output, I provided additional information:
"Consider the following events:
1. Mild recession beginning in 2022, coinciding with rate hikes
2. Recent rate cuts by:
Bank of Canada
Swiss National Bank
3. Rumored upcoming rate cut by: Bank of England
4. Cautious expectations regarding rate cuts by: Federal Reserve (US)"
Initial Tasks and Analysis
I first asked the model to write the index prices into a JSON file.
It extracted the information from the image and created the file accurately.
This initial step already showcased its impressive ability to handle complex tasks involving both vision and data extraction.
It's something that many models struggle with, yet Claude Sonnet 3.5 did it seamlessly, demonstrating its advanced capabilities.
Next, I asked for a detailed correlation analysis and trading strategies: "Impressive. Now I want you to deep dive into the correlations and future predictions. Write a very detailed analysis. Think like the best trader, best hacker, best creative..."
The model goes beyond basic correlations and predictions. It provides context, acknowledges exceptions, and offers a nuanced understanding of complex relationships.
Also, it doesn’t just stop at identifying correlations; the model explains why those relationships exist and under what conditions they might change.
This is particularly useful for traders and analysts who need to understand not just the "what" but also the "why" behind market movements.
Instead of offering a single prediction, the model considers multiple scenarios and their potential impacts.
This is critical for financial analysis, where outcomes are rarely certain, and preparing for various possibilities can be the key to successful trading and investment strategies.
Let's first see how it analyzed the correlations:
---
Correlation Analysis:
a) Federal Funds Rate and U.S. Dollar Index:
There's a generally positive correlation between these two variables. When interest rates rise, the dollar tends to strengthen. This is evident in the period from 2022 to early 2024, where both the Federal Funds Rate and the Dollar Index increased significantly. However, this correlation isn't perfect, as seen in the 2015-2018 period where the dollar weakened despite rising rates.
b) Federal Funds Rate and S&P 500:
The relationship here is more complex. Historically, moderate rate hikes often coincided with bull markets (e.g., 2016-2018). However, rapid rate increases, like those seen in 2022, can lead to market corrections. Interestingly, the S&P 500 has shown remarkable resilience, reaching new highs despite high interest rates in 2023-2024.
c) U.S. Dollar Index and S&P 500:
These two often move inversely, as a stronger dollar can hurt multinational companies' overseas earnings. However, in recent years (2020-2024), we've seen periods where both have risen simultaneously, suggesting other factors (like global economic recovery and tech sector growth) are influencing the S&P 500.
---
The model correctly identifies a general positive correlation between interest rates and the dollar index. This is a well-known relationship because higher interest rates typically attract foreign investment, boosting the dollar.
It mentions periods where this correlation didn’t hold, such as 2015-2018. This kind of insight is invaluable because it warns users that correlations are not absolute and can be influenced by other factors.
Let's continue with the predictions of the model:
---
Future Predictions:
a) Interest Rates:
Given the recent cautious stance of the Federal Reserve, I predict a gradual easing of rates starting in late 2024 or early 2025. The Fed will likely want to see sustained evidence of inflation cooling before making significant cuts. Expect 2-3 rate cuts of 25 basis points each in 2024, bringing the Federal Funds Rate to around 4.75-5% by year-end.
b) U.S. Dollar Index:
As other central banks (Bank of Canada, Swiss National Bank) have already started cutting rates, the dollar may maintain its strength in the short term. However, as the Fed eventually joins the rate-cutting cycle, we could see the Dollar Index retreat to the 98-100 range by end of 2024.
c) S&P 500:
The index has shown remarkable resilience. Given the potential for rate cuts and continued AI-driven tech growth, I predict the S&P 500 could reach 5300-5500 by end of 2024. However, this is contingent on a "soft landing" scenario where inflation is controlled without triggering a severe recession.
---
The model explains that moderate rate hikes can coincide with bull markets, while rapid increases can lead to corrections.
This reflects a sophisticated understanding of how interest rates can impact equity markets differently depending on the rate of change and the broader economic context.
Noting the resilience of the S&P 500 despite high rates in 2023-2024 is an important observation, indicating that other factors, such as technological advancements, might be at play.
While these typically move inversely, the model highlights periods when both rose simultaneously, suggesting other influences like global recovery and tech sector growth.
This is a great example of the model's ability to provide context-specific insights.
I can't wait to feed Anthropic Sonnet 3.5 over the upcoming months, but I can clearly say that you can't get this kind of technical reasoning and valid predictions from GPT-4 or other models. I also really liked the language and tone of the model.
But you know what, it hasn't even started yet.
In the same output, it also provided potential black swan events and algorithmic trade opportunities (I had to use a larger token size because it got cut in half).
But let's check the trading strategy suggestions;
---
Trading Strategies:
a) Yield Curve Trading: With potential rate cuts on the horizon, consider a "steepener" trade, betting on the yield curve steepening as short-term rates fall faster than long-term rates.
b) Sector Rotation: As rates potentially decrease, rotate into sectors that benefit from lower rates, such as Real Estate and Utilities. However, maintain exposure to tech stocks that have shown resilience in various rate environments.
c) Dollar-Sensitive Plays: If the dollar weakens as predicted, look into multinational companies with significant overseas revenue, as well as emerging market ETFs that could benefit from a weaker dollar.
d) Options Strategies: Consider long-dated call options on the S&P 500 to benefit from potential upside while limiting downside risk. Alternatively, use a collar strategy to protect gains while still participating in potential upside.
Potential Black Swan Events:
a) Geopolitical Tensions: Escalation of conflicts in Ukraine or the Middle East could lead to safe-haven flows, strengthening the dollar and potentially causing market volatility.
b) Tech Bubble Burst: The concentration of S&P 500 gains in a few large tech stocks poses a risk. Any significant regulatory action or earnings disappointment could trigger a broader market selloff.
c) Inflation Resurgence: If inflation proves stickier than expected, the Fed might be forced to maintain high rates for longer, potentially triggering a more severe recession.
Algorithmic Trading Opportunities:
a) High-Frequency Trading: Develop algorithms to capitalize on short-term discrepancies between interest rate expectations and currency movements.
b) Machine Learning Models: Train models on historical data to predict S&P 500 movements...
---
Predicting a gradual easing of rates aligns well with current economic conditions and the cautious stance of the Federal Reserve.
This kind of prediction is useful for planning long-term investment strategies.
The detailed forecast of 2-3 rate cuts bringing rates to 4.75-5% by year-end 2024 is precise and actionable, helping investors set expectations and plan accordingly.
The model's prediction of short-term dollar strength followed by a retreat as the Fed cuts rates is logical and reflects an understanding of global monetary policy dynamics.
Providing a specific range (98-100) adds clarity and helps in setting more precise trading strategies.
The prediction of the S&P 500 reaching 5300-5500 is optimistic yet grounded in current trends like AI-driven tech growth. It’s contingent on a “soft landing” scenario, which is a realistic assessment.
Mentioning the conditions (controlled inflation and avoiding a severe recession) shows that the model’s predictions are not just hopeful but based on realistic scenarios.
Yield Curve Trading:
Sophisticated Strategy: Suggesting a steepener trade reflects an advanced understanding of bond markets. This strategy is timely given the potential rate cuts.
Sector Rotation:
Actionable Advice: Rotating into sectors that benefit from lower rates while maintaining tech exposure is a balanced approach, showing the model’s ability to think strategically about portfolio management.
Dollar-Sensitive Plays:
Global Perspective: This strategy leverages the model’s earlier analysis of the dollar index and provides actionable insights for global exposure.
Options Strategies:
Risk Management: The inclusion of options strategies like long-dated call options and collar strategies demonstrates a sophisticated approach to risk management and leveraging opportunities.
Black Swan Events:
Geopolitical Tensions, Tech Bubble Burst, Inflation Resurgence: Identifying these potential black swan events shows the model’s depth of risk analysis, considering various factors that could disrupt markets. This helps traders and investors prepare for unexpected scenarios.
It even touched upon potential Nvidia crashes or AI regulatory affects on the market.
This is just a quick overview of the model, but it's super impressive!
Smarter, faster, cheaper.
Great job @AnthropicAI @alexalbert__
2/11
Great stuff, very impressive results.
3/11
Thank you, Andrew. Super exciting!
4/11
Great tutorial. When you uploaded the data did you add multiple years or just some shorter duration? Simple excel file or some other way.
5/11
I just uploaded this image and asked it to write the prices into a JSON file.
6/11
Great work!
7/11
Thank you
8/11
The S&P is already approaching 5500. When did you write this?
9/11
This is the chart that I used. Probably around Feb March
10/11
Absolutely amazing, thanks for sharing! @didier_lopes FYI
11/11
Thank you. Great opportunity for OpenBB!
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
1/1
Claude 3.5 Sonnet is one of the best models, especially when it comes to logic. The "puzzle" below can hardly be solved by any model. It is one of the questions regularly asked by
@MatthewBerman to test the capabilities of new models. Due to its next-token-prediction architecture, it is very difficult to solve this puzzle.
Sonnet 3.5 made it 0-shot at the first attempt. I am impressed.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
Claude 3.5 Sonnet is one of the best models, especially when it comes to logic. The "puzzle" below can hardly be solved by any model. It is one of the questions regularly asked by
@MatthewBerman to test the capabilities of new models. Due to its next-token-prediction architecture, it is very difficult to solve this puzzle.
Sonnet 3.5 made it 0-shot at the first attempt. I am impressed.
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
Computer Science > Artificial Intelligence
[Submitted on 20 Jun 2024]
Q* - Improving Multi-step Reasoning for LLMs with Deliberative Planning
Chaojie Wang, Yanchen Deng, Zhiyi Lv, Shuicheng Yan, An Bo
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2406.14283 [cs.AI] |
| (or arXiv:2406.14283v1 [cs.AI] for this version) | |
| [2406.14283] Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning |
Submission history
From: Chaojie Wang [ view email][v1] Thu, 20 Jun 2024 13:08:09 UTC (512 KB)