This is a premium 1-click Desktop Cloud Agent you can instantly deploy to our cloud servers using the form to the right. Example blog post on GPT-4: AI's Newest Advancements- GPT-4 and Beyond The AI landscape is witnessing remarkable growth with the emergence of sophisticated models like GPT-4. Tech enthusiasts and industry insiders are fervently discussing the potential and performance of AI giants like OpenAI's GPT-4 and Google Cloud. Recent studies have indicated that GPT-4 not only exhibits an incredible understanding of complex concepts but also outperforms earlier versions in numerous tasks, sparking debates on its prowess versus new competitors like Google Gemini. The advancements go beyond mere comprehension. AI models like GPT-4 now power Microsoft Copilot, bringing AI's capabilities to a wider audience. However, despite free access to such advanced AI, platforms like Microsoft’s Copilot haven't significantly dented the impact of established services like ChatGPT. This raises questions about the true reach and utility of these AI tools in everyday technology use. AI's role in healthcare is also making headlines, with startups initially built on GPT-4 seeking alternatives for more open-source solutions, citing limitations and potential improvements beyond what's currently offered by top-tier providers. The capabilities have even extended into lab environments, where AI-powered assistants are directing complex organic reactions, revolutionizing patient care and matching processes for clinical trials. OpenAI's GPT-4 continues to evolve, becoming an essential tool across various sectors. From generating efficient code to streamlining tasks, businesses and individual users alike are keen on leveraging AI to its fullest potential. The community is also eager to see what the future holds, with discussions on GPT-5 already surfacing alongside news about other smaller yet powerful language models. In summary, the AI revolution is in full swing, with generative models increasingly becoming indispensable tools. As OpenAI's models evolve and new offerings come to the market, the possibilities for innovation and improved efficiency in both personal and professional scenarios seem limitless.
Run Agent
{ "graph":{ "acyclic":false, "pipe_collision":false }, "nodes":{ "0x13737353af0":{ "type_":"nodes.basic.BasicNodeA", "icon":"c:\\Users\\Public\\cheatlayer\\examples\\Move.png", "name":"Start Node 0", "color":[ 13, 18, 23, 255 ], "border_color":[ 74, 84, 85, 255 ], "text_color":[ 255, 255, 255, 180 ], "disabled":false, "selected":false, "visible":true, "width":160, "height":71.2, "pos":[ 0.0, -142.39999999999995 ], "port_deletion_allowed":false, "subgraph_session":{}, "custom":{ "Initial Program":"", "Copy This To Intial Program To Open Chrome":"C:\\Program Files\\Google\\Chrome\\Application\\chrome.exe cheatlayer.com", "Data":"{\"type\": \"Start Node\", \"x\": 0, \"y\": 0, \"Application\": \"C:\\\\Program Files\\\\Google\\\\Chrome\\\\Application\\\\chrome.exe cheatlayer.com\"}" } }, "0x13734babee0":{ "type_":"nodes.basic.BasicNodeA", "icon":null, "name":"Python Code 1", "color":[ 13, 18, 23, 255 ], "border_color":[ 74, 84, 85, 255 ], "text_color":[ 255, 255, 255, 180 ], "disabled":false, "selected":false, "visible":true, "width":160, "height":71.2, "pos":[ 0.0, 0.0 ], "port_deletion_allowed":false, "subgraph_session":{}, "custom":{ "code":"import requests\nimport xml.etree.ElementTree as ET\n\n# Function to fetch latest news on GPT-4 from Google News RSS feed\n\ndef fetch_latest_gpt4_news(topic):\n # Encode the topic to be URL-friendly\n encoded_topic = requests.utils.quote(topic)\n # Google News RSS feed URL for the given search query\n rss_url = f\"https://news.google.com/rss/search?q={encoded_topic}&hl=en-US&gl=US&ceid=US:en\"\n\n # Send a GET request to the RSS feed URL\n response = requests.get(rss_url)\n\n # Check if the request was successful\n if response.status_code == 200:\n # Parse the RSS feed content\n root = ET.fromstring(response.content)\n\n # Find all 'item' elements in the feed\n items = root.findall('.//item')\n\n # Extract the title and link for each news item\n news_items = [{'title': item.find('title').text, 'link': item.find('link').text, 'description': item.find('description').text} for item in items]\n\n return news_items\n else:\n raise Exception(f\"Failed to fetch the RSS feed: {response.status_code}\")\n\n# Function definition for gpt3Prompt (assuming it's predefined)\n# This is just a placeholder for the actual function you should have already defined.\n# It should interact with an AI model to generate content based on the prompt.\n\n\n# Main script execution\nif __name__ == '__main__':\n try:\n # Fetch the latest GPT-4 news\n latest_news = fetch_latest_gpt4_news({{topic}})\n print(latest_news)\n # Concatenate news titles and descriptions to form a prompt for GPT-3\n news_descriptions = '\\n'.join([f\"{item['title']}\\n{item['description']}\" for item in latest_news])\n\n # Use the gpt3Prompt function to generate a blog post\n gpt4_blog_post = gpt3Prompt('Summarize this text into a blog post', news_descriptions)\n\n # Save the blog post to a text file\n with open('{{folder}}/gpt4_blog_post.txt', 'w', encoding='utf-8') as file:\n file.write(gpt4_blog_post)\n \n print('Blog post generated and saved to gpt4_blog_post.txt')\n\n except Exception as e:\n print(f\"An error occurred: {e}\")", "Data":"{\"type\": \"python\"}" } }, "0x137352ce6b0":{ "type_":"nodes.basic.BasicNodeA", "icon":null, "name":"Gmail 2", "color":[ 13, 18, 23, 255 ], "border_color":[ 74, 84, 85, 255 ], "text_color":[ 255, 255, 255, 180 ], "disabled":false, "selected":true, "visible":true, "width":160, "height":71.2, "pos":[ 0.0, 142.4000000000001 ], "port_deletion_allowed":false, "subgraph_session":{}, "custom":{ "key":"655661703861be3664ca7e5b", "to":"{{user}}", "subject":"News To Blog Generator Agent", "file":"gpt4_blog_post.txt", "body":"Please find attached the blog post generated from news on {{topic}}", "Body variable":"", "Data":"{\"type\": \"Email\"}" } } }, "connections":[ { "out":[ "0x13737353af0", "out A" ], "in":[ "0x13734babee0", "in A" ] }, { "out":[ "0x13734babee0", "out A" ], "in":[ "0x137352ce6b0", "in A" ] } ] }
Step 1: Use Cheat Layer on websites to discover new Cheat Codes by asking it to automate what you want.
Step 2: If the custom automation is useful, share it with the community by clicking the "Submit Cheat Code" button.
Step 3: Earn 1,000 Cheat Cloud Points for every Cheat Code you submit! In the future we'll be able to pay creators for every run directly, so users can discover valuable automations using language alone!