[32] Azafran Monthly Headlines

by Magdalena Vuckovic and Jakov Novakovic -

Junior Analysts, Azafran Data Team

The Push to Set the Standards in Regulating AI


As large economies try to fight over reins in artificial intelligence, a new front is opening up around who will set the standards for the snowballing technology.


Earlier this year, China rolled out regulations governing the way online recommendations are generated through algorithms, suggesting what to buy, watch or read. It is the latest barrage in China's efforts to tighten its grip on its tech sector and lays down an important marker in the way that AI is regulated.


China’s moves are significant, given how quickly they were implemented, compared with the timeframes that other jurisdictions typically work with when it comes to regulation. This approach could provide a template to influence other laws internationally.


We can look at China’s AI regulations and the fact that they’re moving first as essentially running some large-scale experiments that the rest of the world can watch and potentially learn something from. While China revamps its rulebook for tech, the European Union is forging its own regulatory framework to control AI, but it has yet to pass the finish line.


The latest European Union AI Act seeks to impose an all-encompassing framework based on the level of risk, which will have far-reaching effects on what products a company brings to market. This European approach will be “more taxing” on companies, compared with the Chinese take, as it will require premarket assessment - in principle, they will be testing products and services before those products or services are being introduced to consumers.


Although the political system and motivations of China will be different from lawmakers in Europe, the technical objectives of both sides bear many similarities — and the West should pay attention to how China implements them.


We shouldn’t try to mimic any of the ideological or speech controls that are deployed in China, but on a technical level, some of these problems are similar in different jurisdictions.


With these two economies presenting AI regulations, the world of AI development and business globally could be about to undergo a significant change.


The market correction has come for Series A


Early-stage businesses are starting to feel the chill after being relatively unscathed by the strain that market volatility has placed on larger digital giants. Market conditions frequently change quickly, but it may take some time for those trends to emerge in a large dataset. However, anecdotal data from individual transactions gives investors a clear indication of the direction of the wind.


Recently, VCs have taken a noticeably more cautious attitude to early-stage investments. Early-stage investors have been more picky, focusing on firms that can fulfill more significant revenue targets than were necessary in the prior two or three months as seed and Series A deal prices have fallen dramatically.


The typical best-in-class Series A deal raised about $20 million last year at a post-money valuation of $120 million. Nowadays these round sizes and valuations have subsequently dropped to roughly $10 million and $50 million, respectively. As a result, founders are agreeing to a greater diluting of their ownership holdings in their own businesses.


Some investors are decreasing values as well as focusing more intently on sales growth. Some VC firms, including Sequoia, are starting to require that businesses show more consistent income before applying for a Series A. Sequoia's spokesman declined to comment.


The minimum required to raise a Series A during the previous three to four years was around $1 million in yearly recurring income. The threshold has now been raised to between $1.5 million and $2 million in ARR. A business can't just show that revenue overnight.


This implies that seed-stage businesses will require more time and money to get their next round of funding.


For example, the seed round ticket amount for Sequoia's Surge will rise to $3 million.

According to Sequoia, which created Surge in 2019 to narrow its emphasis on early-stage financing, boosting the ticket size gives the early-stage entrepreneurs the runway and time they need to achieve product-market fit and build a solid team before raising a Series A.