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  • Writer's pictureGeopolitics.Λsia

Time to Get Real with Artificial Intelligence

Updated: Jan 18

As 2023 draws to a close, the AI landscape has undergone significant transformations since the debut of OpenAI's ChatGPT on November 30, 2022. This pivotal year marks a crucial juncture in the industry's evolution, warranting a comprehensive review. Our focus begins with the unfolding drama in OpenAI's boardroom, as highlighted by The Wall Street Journal and The New Yorker. These publications shed light on internal conflicts and contingency plans involving key figures like Microsoft’s Chief Technology Officer Kevin Scott and CEO Satya Nadella. Despite the high-profile tensions, there's scant evidence to suggest the imminent arrival of sentient AI at OpenAI's labs. The real intrigue lies in the erosion of trust between former board members and CEO Sam Altman, raising questions about the timing and underlying motivations of these boardroom shifts.

Technological advancements are not confined to OpenAI's corridors. The pace of open-source AI development is notably accelerating, as exemplified by French startup Mistral AI's release of their "Breakthrough in Language Models with Mixture of Experts (MoE) 8x7B." This innovation challenges OpenAI's models, including the entry level GPT-3.5, and potentially sets the stage for outpacing even the flagship GPT-4.

We conducted a thorough evaluation of Mixtral's MoE 8x7B chat model and discovered its compliance with requests to generate content typically deemed unethical, such as bioweapon recipes - a type of inquiry standard models routinely reject. This observation raises concerns about potential deficiencies in the model's ethical guardrails.

Google DeepMind's Gemini model, with its various iterations, presents another front in this AI arms race. Although its Pro model outperforms GPT-3.5, the comparison seems underwhelming given GPT-3.5's earlier development timeline and older technology compared to GPT-4. The impending release of Gemini's Ultra version adds another layer of complexity to this competitive landscape.

A recreated version of the Gemini promotional video, where the author employs GPT-4V to achieve identical results, accompanied by transparent source code disclosure.

However, not all developments are technological triumphs. Google recently faced criticism for a promotional video, accused of being misleading, while a developer demonstrated comparable results using just GPT-4V. Moreover, ethical concerns loom large in this rapidly evolving field. Mistral AI's MoE model, while promising, has raised alarms over its ethical guardrails, as evidenced by its potential to generate sensitive content that GPT-3.5 on ChatGPT would reject.

Next, in the regulatory arena, the European Union's pioneering AI law sets a precedent, categorizing AI systems based on risk levels and imposing stringent requirements on high-risk applications and other issues. This legislation echoes the impact of the EU’s General Data Protection Regulation (GDPR), potentially shaping global standards in AI governance.

Comprehensive Infographic Summarizing the Research Papers Presented at NeurIPS 2023

Additionally, the 2023 The Conference and Workshop on Neural Information Processing Systems (NeurIPS), alongside The International Conference on Machine Learning (ICML) and The International Conference on Learning Representations (ICLR,) the conference stands as one of the three major events with significant impact in the realms of machine learning and artificial intelligence research, presents an opportunity to reflect on the AI research community's direction. Among 3,586 papers, A notable award-winning paper, "Are Emergent Abilities of Large Language Models a Mirage?", hints at a paradigm shift for 2024: a move towards refining and optimizing current AI models rather than merely scaling them. This approach, emphasizing techniques like Mixture of Experts (MoE), enhanced prompting technique, notable efficient small model (such as Microsoft's Phi-2) and PathFinder, aligns with a strategic shift towards smarter, more efficient, and versatile AI development. This evolution signifies a commitment to enhancing AI's quality and utility, transcending the pursuit of sheer computational power. Our projection for 2024 aligns with Sam Altman's earlier statements, “I think we’re at the end of the era where it’s gonna be these giant models, and we’ll make them better in other ways."

Finally, OpenAI, through its Twitter presence, has recently acknowledged ongoing investigations into a peculiar 'laziness' observed in GPT-4, the core engine of its widely acclaimed chatbot, Chat GPT. Despite no significant updates being implemented since November 11, user reports indicate an unexpected shift in GPT-4's responsiveness. OpenAI clarifies that the large language model's behavior is inherently unpredictable, shaped by its interactions with users. Such models, even when trained to industry benchmarks, do not guarantee absolute consistency, with varying outcomes emerging from each training iteration.

OpenAI further underscores that this change does not imply the AI's self-modification but rather reflects nuanced reactions to specific user inputs. Thorough investigation into these behavioral nuances is ongoing. This development has also caught the attention of Ars Technica, a prominent IT news outlet, which highlighted a user tweet showing a marked decline in GPT-4's response rates.

An intriguing theory, termed the "winter break hypothesis," posits that the AI's performance dip mirrors a seasonal slowdown in human activity. To probe this theory, we deployed a custom AI (Plain GPT) to inquire if AI performance varied seasonally. The response was unequivocal: AI efficiency remains constant, unaffected by seasonal changes, always operating at peak capability.


Note: As we enter the crucial final phase of revamping our business model and accelerating the launch of our beta product, we are adjusting our reporting approach. Our updates will be more concise, tailored to align with our current resource allocation. Despite this change, rest assured that our coverage will continue to capture the core dynamics of the AI development landscape with the same comprehensive depth as always. We appreciate your continued support and engagement. Please stay tuned for further developments, and look forward to our return to full-length reporting once our final product reaches completion.


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