Scaling in AI has noticeably slowed, challenging the assumption that simply increasing data and compute will lead to advancements like AGI. Insights reveal limitations in data availability and architectural shortcomings, suggesting that the current approach may not be sufficient. The ongoing experiment to create AGI through these means has proven costly and largely ineffective, prompting a call for innovative strategies moving forward.
