If California is the political fundraising powerhouse of the nation, Silicon Valley has grown into one of the increasingly dominant forces of campaign cash. And while Northern California tech entrepreneurs overwhelmingly support Democratic candidates, a small but powerful group of defectors has moved rightward in recent years. A gathering of tech's conservative cohort enjoyed a visit from former President Trump on Thursday evening at a tony fundraiser held at venture capitalist David Sacks' San Francisco home. The estate, nestled on Billionaires' Row in Pacific Heights, welcomed about 80 elites to the sold-out event. Cost of admission: up to 300,000 per person and 500,000 per couple, according to an invitation obtained by The Times.

This article is from Big Technology, a newsletter by Alex Kantrowitz. It's been a year of glossy profiles, breathless accolades, and billions in new funding for OpenAI, but the ChatGPT maker is far more vulnerable than the popular narrative suggests. Amid a seemingly unstoppable ascent, the company is facing fierce competition, a rising open-source movement, and pressure to deliver hits in an unpredictable discipline. While its marquee product has become practically synonymous with A.I., its perch atop the field is less than rock solid. OpenAI's weakness stems in part from its strength. It popularized generative A.I. by taking others' innovations--like the transformer model--and building stellar products on top of them.

Traditional initialisation methods, e.g. He and Xavier, have been effective in avoiding the problem of vanishing or exploding gradients in neural networks. However, they only use simple pointwise distributions, which model one-dimensional variables. Moreover, they ignore most information about the architecture and disregard past training experiences. These limitations can be overcome by employing generative models for initialisation. In this paper, we introduce two groups of new initialisation methods. First, we locally initialise weight groups by employing variational autoencoders. Secondly, we globally initialise full weight sets by employing graph hypernetworks. We thoroughly evaluate the impact of the employed generative models on state-of-the-art neural networks in terms of accuracy, convergence speed and ensembling. Our results show that global initialisations result in higher accuracy and faster initial convergence speed. However, the implementation through graph hypernetworks leads to diminished ensemble performance on out of distribution data. To counteract, we propose a modification called noise graph hypernetwork, which encourages diversity in the produced ensemble members. Furthermore, our approach might be able to transfer learned knowledge to different image distributions. Our work provides insights into the potential, the trade-offs and possible modifications of these new initialisation methods.

China had its sputnik moment in March 2016. That month an artificial intelligence programme, AlphaGo, beat a South Korean grandmaster at Go, an extremely complex and demanding Chinese board game. The five game series was watched by an audience of more than 280 million viewers across China. In May 2017 AlphaGo defeated China's 19-year-old prodigy Ke Jie; two months later the Chinese government issued an AI strategy which projected that the country would become the global centre of AI innovation by 2030. By year's end, China accounted for nearly half of all AI venture funding globally.

China's startup ecosystem, which produced several world-leading companies, has been in the news in the recent past about the impact of the government regulations on the big technology firms. However, despite the regulatory shakeups and the COVID-19 pandemic notwithstanding, China has emerged as a powerhouse for artificial intelligence (AI) unicorns, according to Thematic Research at GlobalData, a leading data, and analytics company. GlobalData's research shows that of the total of 45 AI unicorns globally, China has the biggest share with 19 unicorns headquartered in the country. These 19 unicorns are collectively valued at $43.5bn. Priya Toppo, Analyst of Thematic Research at GlobalData, comments: "China is a leading player in AI, with a number of established companies such as Baidu, Hikvision, iFlytek, Tencent, and Alibaba. The country also has a strong AI startup ecosystem, which is evident from the large number of AI unicorns (privately held startup valued at $1bn or more)."

Proving that Central and Eastern Europe remains a powerhouse of hardware engineering matched with software, Gideon Brothers (GB), a Zagreb, Croatia-based robotics and AI startup, has raised a $31 million Series A round led by Koch Disruptive Technologies (KDT), the venture and growth arm of Koch Industries Inc., with participation from DB Schenker, Prologis Ventures and Rite-Hite. The round also includes participation from several of Gideon Brothers' existing backers: Taavet Hinrikus (co-founder of TransferWise), Pentland Ventures, Peaksjah, HCVC (Hardware Club), Ivan Topčić, Nenad Bakić and Luca Ascani. The investment will be used to accelerate the development and commercialization of GB's AI and 3D vision-based "autonomous mobile robots" or "AMRs". These perform simple tasks such as transporting, picking up and dropping off products in order to free up humans to perform more valuable tasks. The company will also expand its operations in the EU and U.S. by opening offices in Munich, Germany and Boston, Massachusetts, respectively.

Proving that Central and Eastern Europe remains a powerhouse of hardware engineering matched with software, Gideon Brothers (GB), a Zagreb, Croatia-based robotics and AI startup, has raised a $31 million Series A round led by Koch Disruptive Technologies (KDT), the venture and growth arm of Koch Industries Inc., with participation from DB Schenker, Prologis Ventures, and Rite-Hite. The round also includes participation from several of Gideon Brothers' existing backers: Taavet Hinrikus (co-founder of TransferWise), Pentland Ventures, Peaksjah, HCVC (Hardware Club), Ivan Topčić, Nenad Bakić, and Luca Ascani. The investment will be used to accelerate the development and commercialization of GB's AI and 3D vision-based'autonomous mobile robots' or'AMRs'. These perform simple tasks such as transporting, picking up, and dropping off products in order to free up humans to perform more valuable tasks. The company will also expand its operations in the EU and US by opening offices in Munich, Germany and Boston, Massachusetts, respectively.

During the spring semester of my junior year in college, I had the opportunity to study abroad in Copenhagen, Denmark. I had never been to Europe before that, so I was incredibly excited to immerse myself into a new culture, meet new people, travel to new places, and, most important, encounter a new language. Now although English is not my native language (Vietnamese is), I have learned and spoken it since early childhood, making it second-nature. Danish, on the other hand, is an incredibly complicated language with a very different sentence and grammatical structure. Before my trip, I tried to learn a bit of Danish using the app Duolingo; however, I only got a hold of simple phrases such as Hello (Hej) and Good Morning (God Morgen).

There has been a rapid increase in the adoption and development of artificial intelligence across the globe. Business platforms are depending on AI for better growth, efficiency, and digital transformation. Cutting-edge technologies like 5G will escalate the use cases of AI across industries. According to McKinsey Global Survey 2020, 50% of respondents reported that their companies have adopted AI in at least one business function. The global leaders in AI adoption, research, and development include Asian countries like China, Singapore, and Japan.

World's most populous country lacks the one thing it needs to become an AI powerhouse: enough talented people