Recruiter's AI Digest #73
Resources and perspectives to keep you ahead of the curve as AI deepens its impact in Recruiting. 🤖
Welcome to the community of 3,800 forward-thinking recruiting leaders. 🎉 We stay on the pulse of AI and its impact on recruiting, so you don’t have to!
This week’s digest
AI News This Week:
AI News This Week: DeepSeek Fallout, Big Tech's AI Spending, and Regulatory Moves
🔹 DeepSeek Under Scrutiny – DeepSeek, the Chinese AI model, is facing increasing global restrictions over security concerns. The U.S. government is considering a ban on its use in federal agencies, while major Australian companies, including banks and telecom firms, have blocked access to the tool. Concerns over data privacy and potential ties to the Chinese government are driving these moves. (AP, The Australian)
🔹 Big Tech Ramps Up AI Spending – Amazon, Microsoft, Alphabet, and Meta are on track to spend over $320 billion on AI infrastructure in 2025. This marks a significant increase from last year, highlighting their focus on expanding data centers, developing new AI models, and strengthening cloud computing capabilities. (FT)
🔹 ByteDance’s New AI Tool Raises Concerns – The parent company of TikTok has unveiled OmniHuman, an AI-powered video generator capable of creating realistic human avatars from a single image and voice recording. While the technology has potential for entertainment and education, experts warn it could be used for deepfakes and misinformation. (NY Post)
🔹 EU Moves Closer to AI Regulation – The European Union is finalising sweeping AI legislation aimed at regulating AI deployment across industries. The law is expected to set strict rules for high-risk applications, including hiring algorithms and biometric surveillance, while promoting transparency in AI systems used for critical decision-making. (FT)
Articles this week 📖 :
1️⃣ AI-powered job posts
(Metaview)
2️⃣ Workday Cuts 1,750 Jobs in AI Investment Shift
(Reuters)
3️⃣ AI and Automation Enhance the Human Touch in Recruiting
(Forbes)
4️⃣ OpenAI founding member breaks Down How AI Models Work
(Andrej Karpathy)
5️⃣ DeepSeek R1: The Reality Behind the AI Hype
(Y Combinator)
1️⃣ AI powered Job Posts
(Metaview)
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2️⃣ Workday Cuts 1,750 Jobs in AI Investment Shift (Reuters)
Workday is laying off 1,750 employees (8.5% of its workforce) as part of a strategic shift toward AI-driven solutions. The move aims to free up resources for AI investments and expand internationally, despite a softer economic environment. While Workday’s stock rose 4% following the announcement, the company expects up to $270M in restructuring costs. The layoffs follow a trend of HCM industry consolidation, with Paychex acquiring Paycor for $4.1B and ADP purchasing WorkForce Software for $1.2B.
3️⃣ AI and Automation Enhance the Human Touch in Recruiting (Forbes)
AI isn’t replacing recruiters—it’s making their jobs faster and more efficient, allowing them to focus on relationship-building and strategic hiring. Here’s how AI is making a real impact:
AI Speeds Up Hiring – Recruiters using AI-driven tools saw an 80% increase in efficiency. AI handles CV screening, interview scheduling, and candidate outreach, and interview notetaking reducing time-to-hire.
Data-Driven Hiring – AI analyzes recruitment trends, job descriptions, and candidate pipelines to forecast hiring needs and identify biases. Companies can adjust strategies in real time based on AI insights.
Better Candidate Experience – 76% of job seekers say a smooth hiring process influences their decision to accept an offer. AI chatbots answer candidate questions 24/7, while automated updates reduce frustration during long hiring processes.
AI + Recruiters = Best of Both Worlds – AI can’t replace cultural fit assessments, complex negotiations, or human intuition. Instead, it automates the repetitive tasks, freeing recruiters to focus on meaningful candidate interactions.
Read more on Forbes.
4️⃣ Andrej Karpathy Breaks Down How AI Models Work
For anyone who truly wants to understand how something like ChatGPT works, here’s some weekend watching for….
AI expert Andrej Karpathy, former OpenAI founding member and Tesla’s AI lead, released a 3+ hour deep dive on how models like ChatGPT work. He covers pre-training, tokenization, reasoning, and reinforcement learning—explaining how AI processes information, improves through training, and why models still struggle with reasoning.
Key takeaways:
AI learns from filtered internet data (~44TB of high-quality text).
Tokenization breaks words into ~100,000 pieces for efficient processing.
Reasoning models like DeepSeek R1 and OpenAI’s latest models use reinforcement learning to simulate step-by-step problem-solving.
Future AI will integrate text, audio, and images seamlessly and handle long-running tasks independently.
5️⃣ DeepSeek R1: The Reality Behind the AI Hype
DeepSeek’s R1 reasoning model sparked a media frenzy, but the underlying tech isn’t new. The model builds on DeepSeek V3, released in December, optimizing for efficiency and reasoning tasks. Despite claims of state-of-the-art performance at low cost ($5.5M training run), experts note this figure excludes R&D and operational expenses.
DeepSeek’s key innovations:
8-bit floating point training (saves memory, speeds up computation).
Mixture of Experts (MoE) (activates fewer parameters per prediction, cutting costs).
Reinforcement learning techniques (improves step-by-step reasoning).
While DeepSeek’s open-source approach makes it accessible, newer models like OpenAI’s GPT-4o have already surpassed its benchmarks. The real impact? Lower AI costs and greater accessibility, pushing AI research and applications forward.
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