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Possible consequences of current developments

  1. Multiple first-author papers in top ML conferences, but still struggling to get into a PhD program. What am I missing?

    • Benefits: Having multiple first-author papers in top ML conferences demonstrates a strong research background and expertise in the field. This can help the individual stand out and potentially secure better job opportunities in industry or academia.

    • Ramifications: Struggling to get into a PhD program may indicate a misalignment between the applicant’s research interests and the programs they are applying to. It could also be a result of limited networking or mentorship opportunities, lack of diversity in research experience, or not meeting specific program requirements. The individual may need to seek guidance from mentors, broaden their research portfolio, or improve their application materials to increase their chances of acceptance.

  2. Publication rat race for PhD in ML

    • Benefits: The publication rat race can drive researchers to produce high-quality and impactful work, pushing the boundaries of knowledge in the field of ML. This can lead to advancements in technology, improved research methodologies, and a competitive edge for individuals in academia or industry.

    • Ramifications: The intense pressure to publish frequently and in top-tier venues can contribute to research misconduct, burnout, and a focus on quantity over quality. It may also create barriers for newcomers or underrepresented groups in the field, perpetuating inequalities and hindering diversity in ML research. Finding a balance between productivity and well-being is crucial to avoid negative consequences.

  • Recommendations please: which SMALL LLM to use to handle basic chat functionality plus JSON input and JSON Output
  • Using CLIP for knowledge distillation without a teacher model, using only teacher embeddings
  • Researchers at Apple Propose MobileCLIP: A New Family of Image-Text Models Optimized for Runtime Performance through Multi-Modal Reinforced Training
  • Are LLMs good at NL-to-Code & NL-to-SQL tasks?

GPT predicts future events

  • Artificial General Intelligence: (2035)

    • I predict that we will see the first inklings of artificial general intelligence around this time because advancements in artificial intelligence technology are accelerating at a rapid pace. Researchers are making strides in creating systems that can perform a wide range of cognitive tasks, and it is only a matter of time before we achieve AGI.

  • Technological Singularity: (2050)

    • The technological singularity, where superintelligent AI surpasses human intelligence and accelerates progress at an unprecedented rate, is likely to occur around this time because advancements in AI, robotics, and other technologies are converging. With the exponential growth of technology, it is projected that we will reach a point where machines exceed human cognitive capabilities.