The Nvidia Selloff - September 03, 2024

 

• Nvidia has started this September in an inauspicious way — with its a huge daily selloff since April. The stock is now off about 20% from its all-time closing high of $135.58, as its recent earnings report made investors jittery about its future margin performance and whether it can keep up its big beats. (MarketWatch 09/04/2024)
• Nvidia CEO and co-founder Jensen Huang's fortune shrank by nearly $10 billion after the chipmaker’s share price fell amid a wider selloff of major tech stocks on September 03, 2024. (Forbes, 09/04/2024)
• Justice Department takes a major step toward an antitrust lawsuit against Nvidia. Officials are investigating whether Nvidia's dominance has made it difficult for buyers to use other suppliers, some complained that Nvidia threatens clients that use chips from both Nvidia and its competitors. (Business Insider, 09/04/2024)
• [Factcheck] Nvidia dictates how chips are allocated to stop companies from stockpiling them amid limited supply. Installing the chips the way Nvidia wanted would have reportedly hindered. Microsoft's ability to switch to different AI chips. Microsoft eventually won out when Nvidia backed down and agreed to let the Big Tech company design its own custom racks. (Business Insider, 06/20/2024)
• [Factcheck] Intel’s Xeon processors are capable of more complex data crunching, but they have fewer cores and are much slower for processing information typically used to train AI software. AMD announced an updated version of its MI300 AI processor would go on sale in Q4. But Nvidia’s advantage isn’t just in the performance of its hardware. Its CUDA, a language for its graphics chips that allows them to be programmed for the type of work that underpins AI programs.(QuickTake, 06/07/2024)

The AMD MI300X and Nvidia Blackwell are both cutting-edge AI processors, each with unique strengths and features. Here’s a comparison based on the latest information (prepared by an AI):

AMD MI300X

• Architecture: Built on AMD’s CDNA 3 architectures
• Compute Units: 304 compute units.
• Memory: 192 GB of HBM3 memory with a peak bandwidth of 5.3 TB/s.
• Performance: Known for its strong performance in FP8 floating point calculations and HPC-centric double precision workloads. It boasts impressive cache bandwidth and latency, outperforming Nvidia’s H100 in several benchmarks.
• Power Consumption: 750W.

Nvidia Blackwell

• Architecture: Successor to the H100, designed to leapfrog AMD in performance.
• Compute Units: Details on compute units are less specific, but it integrates compute and IO into each chip.
• Memory: 192 GB of high bandwidth memory, with a memory bandwidth of 2.8 TB/s.
• Performance: Excels in sparse performance, delivering 45 teraFLOPS of FP64 tensor core performance. It is optimized for AI inferencing and lower precision tasks.
• Power Consumption: 700W.

Key Differences

• Memory Bandwidth: MI300X has a higher memory bandwidth (5.3 TB/s) compared to Blackwell (2.8 TB/s), which can be crucial for AI performance.
• Compute Performance: MI300X shows a significant advantage in double precision performance, while Blackwell excels in sparse performance and lower precision tasks.
• Power Efficiency: Blackwell is slightly more power-efficient with a 700W consumption compared to MI300X’s 750W.
• Both processors are designed to handle demanding AI workloads, but their strengths lie in different areas. The choice between them would depend on the specific requirements of the tasks at hand.

References

• AMD's customers begin receiving the first Instinct MI300X AI GPUs — the company's toughest competitor to Nvidia's AI dominance is now shipping
• Nvidia Blackwell vs. MI300X : r/AMD_Stock (reddit.com)
• AMD MI300X performance compared with Nvidia H100 — low-level benchmarks testing cache, latency, inference, and more show strong results for a single GPU | Tom's Hardware (tomshardware.com)
• Nvidia Launches Next-Generation Blackwell GPUs Amid AI ‘Arms Race’ (datacenterknowledge.com)
• Nvidia turns up the AI heat with 1,200W Blackwell GPUs • The Register

俄罗斯进行大规模空袭 Moscow Rains Fire on Ukraine

2024年8月26日，俄军向乌克兰发射了百余枚火箭弹和无人机。乌克兰总统泽连斯基呼吁西方盟友允许基辅使用西方提供的远程自卫武器打击俄罗斯境内的军事目标。值得注意的是，美国禁止乌克兰使用远程ATACMS导弹袭击俄罗斯领土。

俄罗斯的这次袭击再次以关键民用基础设施为目标。关键基础设施包括能源部门和铁路。这次袭击至少造成 7 人死亡，47 人受伤。47 名伤者中有 4 名是儿童。

截至目前，俄羅斯自2022年2月起入侵烏克蘭，已造成數十萬軍人傷亡和數萬烏克蘭平民傷亡。具體而言，自入侵開始以來，俄羅斯軍隊已損失超過 606,000 名士兵。此外，聯合國人權事務高級專員辦事處已核實共有 35,160 名平民傷亡和 23,640 人報告受傷。衝突仍在繼續，俄羅斯軍隊目前佔領了烏克蘭約 20% 的領土。對平民的影響是巨大的，數百萬人流離失所，難民危機堪比二戰。

2022 年 8 月 8 日，皇家联合服务研究所 (RUSI) 发布了一份报告，称大多数明显的西方组件都是由美国公司制造的。这可能是因为俄罗斯的战争机器严重依赖进口复杂的微电子产品才能有效运行。 而 2023 年 10 月 3 日，PBS 新闻的 Simon Ostrovsky 报道称，俄罗斯坦克的一个机器部件是由一家位于纽约的公司制造的。 

根据 Julia Monn 和 Katrin Büchenbacher 的报道，一些国家向俄罗斯提供机器和零部件，例如电子产品、可用于制造武器的建筑材料或无人机/导弹。 而印度刚刚在 2024 年 7 月超过中国，成为俄罗斯石油全球最大进口国。这就是泽连斯基敦促印度停止进口俄罗斯石油的原因。泽连斯基也点名中国在俄罗斯对乌克兰战争中扮演的角色。

Russian forces launched over a hundred rockets and drones at Ukraine on August 26, 2024. Ukrainian defenders managed to destroy 102 enemy rockets and 99 drones. Ukrainian President Volodymyr Zelenskyy has urged Western allies to allow Kyiv to strike military targets inside Russia using Western-supplied longer-range weapons in self-defense. It is worth noting that the US prohibits Ukraine from using its long-range ATACMS missiles for strikes on Russian territory. (RBC Ukraine, 08/26/2024)

This Russian strike again targeted critical civilian infrastructure. The critical infrastructure includes the energy sector and railroads. At least seven people were killed and at least 47 others injured from this strike. Out of the 47 people injured, four were children. (abcNews, 08/26/2024)

Up to now, Russia's invasion of Ukraine since February 2022 has caused hundreds of thousands of military casualties and tens of thousands of Ukrainian civilian casualties. Specifically, the Russian military has lost over 606,000 soldiers since the invasion began1. Additionally, the Office of the United Nations High Commissioner for Human Rights has verified a total of 35,160 civilian casualties and 23,640 reported injured2. The conflict continues, with Russian forces currently occupying approximately 20% of Ukraine’s territory3. The impact on civilians is huge, with millions displaced and a refugee crisis comparable to World War II. (1-4)

On August 08, 2022, the Royal United Services Institute (RUSI) released a report that the majority of the apparent Western components were manufactured by U.S. companies. It is probably because the Russia's war machine is heavily reliant on imports of sophisticated microelectronics to operate effectively. (RUSI, 08/08/2024) While on October 03, 2023, Simon Ostrovsky at PBS News reported that a machine part of the Russian tanks was made by a company based in New York. (PBS News, 10/03/2023) \

According to Julia Monn and Katrin Büchenbacher's report, one Russia's ally supplies Russia with machines and components such as electronics, building materials that can be used to build weapons. (NZZ, 05/23/2024) While two others provide drones and/or missiles. (Financial Times, 01/13/2024) On the other hand, India has just overtaken China as the world's largest importer of Russian oil in July 2024. (The Kyiv Independent, 08/23/2024) This is why Zelenskyy urges India to halt Russian oil imports. (The New Voice of Ukraine, 08/25/2024) Zelenskyy also calls out China's role in Russia's War on Ukraine. (The Diplomat, 06/04/2024)

References

1. Ukraine civilian war casualties 2024 | Statista

2. Russian invasion of Ukraine - Wikipedia

3. Russia Launches 'One Of The Heaviest Strikes' On Ukraine In Over 30 Months Of War: Zelensky - Benzinga

4. Casualties of the Russo-Ukrainian War - Wikipedia

Moscow Rains Fire on Ukraine 

Six killed in 'most massive' Russian air attack

Microsoft Copilot vs. Google Gemini: A Comparison

I asked Microsoft Copilot to compare Microsoft Copilot with Google Gemini. Here is its answer:

Microsoft Copilot and Google Gemini are both AI chatbots, but they serve different purposes and have distinct features. Here’s a brief comparison:

Microsoft Copilot:

• Integrated into Microsoft 365 apps.
• Powered by OpenAI’s GPT-3.5 and GPT-4 Large Language Models (LLMs).
• Suitable for collaboration within Microsoft apps like Outlook, Word, PowerPoint, and Excel.
• Excellent quality output with impressive factual accuracy and responsiveness to feedback.
• Cluttered interface but comprehensive integration with Microsoft 365 tools1.
• If you create text, images, spreadsheets, or presentations in Microsoft 365 apps, Copilot is a good choice.

Google Gemini:

• Replaced Google’s Bard in 2024.
• Powered by the Gemini LLM.
• Designed to integrate with Google Workspace apps (documents, presentations, spreadsheets, and mail).
• Good quality output in creative writing and editing tasks, but constant fact-checking is needed.
• Already an eloquent assistant for creative writing tasks.
• If you primarily work in Google Docs, Gemini is worth considering.

In terms of user base, specific numbers aren’t readily available. However, if you’re a regular user of Google services and apps, Google Duet might be better for you. If you use Teams and Microsoft Office applications, Copilot is the better choice. Additionally, Copilot offers an advantage in terms of internet connectivity and up-to-date information retrieval3. Ultimately, the choice depends on your specific needs and preferences.

Then, I asked the question to Google Gemini. Here is the answer:

Microsoft Copilot and Google Gemini are both powerful AI assistants designed to enhance productivity and streamline workflows.  While they share many similarities, there are key differences that set them apart.  

Key Differences

• Integration: Copilot is deeply integrated into the Microsoft 365 ecosystem, providing assistance across applications like Word, Excel, PowerPoint, and Outlook. Gemini, on the other hand, is more versatile and can be used across various platforms and applications.   
• Focus: Copilot primarily focuses on productivity tasks, such as drafting emails, creating presentations, and summarizing documents. Gemini offers a broader range of capabilities, including text generation, translation, and coding.  
• Source icon
• Language Model: Copilot is built on the GPT-4 language model, while Gemini is powered by Google's proprietary Pathways language model. Both models are highly advanced, but their specific strengths and weaknesses may vary.

Similarities

• Natural Language Processing: Both Copilot and Gemini can understand and respond to natural language prompts, making them easy to use for users of all skill levels.
• Learning Capabilities: Both assistants can learn from their interactions with users, improving their performance over time.
• Task Automation: Both can automate repetitive tasks, freeing up users to focus on more complex work.

In conclusion, both Microsoft Copilot and Google Gemini are powerful AI assistants that can significantly enhance productivity. The best choice for you will depend on your specific needs and preferences. If you are deeply invested in the Microsoft ecosystem and primarily need assistance with productivity tasks, Copilot may be the better option. If you require a more versatile AI assistant with a wider range of capabilities, Gemini could be a good fit.