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- š¤ āI Applied to 2,843 Jobsā Using AI in Under Three Months
š¤ āI Applied to 2,843 Jobsā Using AI in Under Three Months
PLUS: Writerās New Autonomous AI Employee?!, LLMs Create Their Own Reality to Improve Generative Abilities
Welcome back AI enthusiasts!
In todayās AI Report:
šāI Applied to 2,843 Jobsā Using AI in Under Three Months
š¦¾Writerās New Autonomous AI Employee?!
šLLMs Create Their Own Reality to Improve Generative Abilities
š Trending Tools
š°Funding Frontlines
š¼Whoās Hiring?
Read Time: 3 minutes
šRECENT NEWS
AI SPAMMING
šāI Applied to 2,843 Jobsā Using AI in Under Three Months
According to 404 Media, a person leveraged AI Hawkās āAuto Jobs Applierā to automate the job application process for 2,843 job openings in under three months.
Key Details:
Auto-Jobs-Applier-AIHawk is a trending tool on GitHub thatās actively being used by thousands of people to apply for multiple job openings at once.
It relies on a Python Script (i.e., a programming language) that navigates LinkedIn job postings and uses OpenAIās GPT-4 to generate cover letters or resumes based on job descriptions.
The success of AI Hawkās āAuto Job Applierā has inspired copycats, including JobMagic, whose tagline is āapply for jobs while you sleep.ā
Why Itās Important:
The rise of AI-powered job application bots enables job seekers to think like spammers; the more job offerings I apply to, the higher my odds of landing a job.
With so many Big Tech job applications being reviewed by AI software, itās not surprising that several people have embraced using AI Hawkās āAuto Job Applier.ā
š©ŗ PULSE CHECK
How will AI-powered job application bots impact the job market?Vote Below to View Live Results |
WRITER
š¦¾Writerās New Autonomous AI Employee?!
Image Source: Canvaās AI Image Generators/Magic Media
Writer, a startup building secure AI applications for business processes, released a new AI framework called āPalmyra X 004.ā
Key Details:
āPalmyra X 004ā enables AI models to perform actions in external systems, such as updating databases, triggering workflows, and sending emails, by using Tool Calling.
Tool Calling allows AI models to interact with other platforms and autonomously perform tasks.
āPalmyra X 004ā features Automatic Data Integration (ADI) with Retrieval-Augmented Generation (RAG), Chain-of-Thought (CoT), and Source Transparency.
ADI integrates data from various sources into an AI model without manual intervention.
RAG is a technique that improves the accuracy of AI models by pulling relevant, up-to-date data directly related to a userās query.
CoT encourages AI models to break down complex problems into manageable steps.
Source Transparency outlines an AI modelās decision-making process when generating responses.
āPalmyra X 004ā achieved 78.76% accuracy on Berkleyās Function-Calling Leaderboard (BFCL), which evaluates how well AI models interact with software tools. In comparison, OpenAIās GPT-4o (āoā for āomniā) achieved 59.29% accuracy.
Why Itās Important:
Conversational chatbots provide us with information to help us make decisions by answering open-ended questions with limited context.
In contrast, āPalmyra X 004ā can operate autonomously across websites, apps, and data types (e.g., text, image, audio, video, and code).
Conversational chatbots enhance marginal productivity, but āPalmyra X 004ā eliminates swaths of digital work by automating workflows.
AI RESEARCH
šLLMs Create Their Own Reality to Improve Generative Abilities
Image Source: MIT CSAIL/āLatent Casual Probing: A Formal Perspective on Probing With Casual Models of Dataā/Screenshot
If you ask Large Language Models (LLMs) like OpenAIās GPT-4 to smell a rain-soaked campsite, itāll decline.
However, if you ask the same LLM to describe the smell of a rain-soaked campsite, itāll generate detailed descriptions of āan air thick with earthy anticipation.ā
So, how do LLMs generate these detailed descriptions? When exploring this question, MIT CSAIL researchers discovered that LLMs may develop their own understanding of reality to improve generative abilities.
They created a dataset of small Karel Puzzles that test an LLMās ability to execute instructions in simulated environments. Karel Puzzles involve controlling a robot named Karel to navigate a grid world and perform specific tasks like moving, turning, and rotating objects.
After training an LLM on over one million Karel Puzzles, they found that it developed its own reality of the simulated environments. These findings suggest that LLMs might be able to extract meaning from language beyond just surface-level patterns.
š TRENDING TOOLS
šŖScribe turns any process into a step-by-step guide.
šŖ¶SmartWriter generates cold emails that get you replies.
šSemanticScholar is a research tool for scientific literature.
š§ SecondBrain is your personal knowledge management system.
šØadsby optimizes every click to maximize results with Google Ads.
š®Browse our always Up-To-Date AI Tools Database.
š°FUNDING FRONTLINES
Third Dimension AI raises a $7M Seed Fund to build AI-enabled game worlds.
Q-CTRL adds $59M to a $113M Series B to scale quantum computing software.
Basecamp Research secures a $60M Series B to fuel AI advancements in life sciences.
š¼WHOāS HIRING?
Weber Shandwick (New York City, NY): Capital Markets Intern, Spring 2025
Verkada (San Mateo, CA): iOS Engineering Intern, Summer 2025
Waymo (Mountain View, CA): Full-Stack Software Engineer Intern, Labeling Platform, Summer 2025
Magical (Remote): Front-End/Full-Stack Software Engineer, New College Grad 2024
NVIDIA (Santa Clara, CA): Applied Machine Learning {ML} Engineer, Very Large Scale Integration {VLSI} Design, New College Grad 2024
š¤PROMPT OF THE DAY
MARKETING
šCreate Taglines and Slogans
Generate several taglines for [Business] with [Product/Service] in [Industry] that use a play on words.
Keep it short, memorable, and aligned with our brand identity. It should be easy to remember and effectively communicate our value to potential customers.
Business = [Insert Here]
Product/Service = [Insert Here]
Industry = [Insert Here]
šFINAL NOTE
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