"Elon Musk is working on the most important areas of A.I. xAI is working on foundation cognitive intelligence A.I., Tesla is working on autonomous vehicles. Optimus is for humanoid robotics. He is very optimistic about the future of A.I."https://t.co/TdQGLZ228a ...

Tesla Trade - Ark Invest sold 27,102 shares of Tesla from its ARK Innovation ETF, with the stock closing at $426.58, up by 1.71% on the day [2] - The sale occurred after Tesla's market cap increased by $90 billion, driven by enthusiasm for its AI and autonomous vehicle initiatives, despite mixed signals from its latest quarterly results [3] - The total value of the Tesla shares sold is approximately $11.6 million [3] Coinbase Trade - Ark Invest increased its position in Coinbase by purchasing 62,166 shares across multiple ETFs, with Coinbase's stock closing at $264.97, marking a 4.27% increase [4] - Despite strong third-quarter results, including $1.9 billion in revenue and $1.50 EPS, Argus Research downgraded Coinbase to Hold due to stretched valuations, noting it trades at 39 times its 2026 earnings forecast [5] - The total value of the Coinbase shares purchased is nearly $16.5 million [4] Deere & Co Trade - Ark Invest acquired 30,518 shares of Deere & Co. across various ETFs, with Deere's stock closing at $469.87, down by 5.67% following its fourth-quarter earnings report [6][7] - Deere reported EPS of $3.93 and quarterly sales of $12.39 billion, both exceeding expectations, with revenue up 11% year over year [7] - The total value of the Deere shares bought is approximately $14.3 million, indicating a strategic bet on the company's future recovery [8]

Core Insights - Tesla CEO Elon Musk has expressed ambitious plans to produce chips at higher volumes than all other AI chips combined, following the approval of a $1 trillion pay package by shareholders [1] - The strategy centers around artificial intelligence, which is crucial for Tesla's goals in autonomous vehicles, humanoid robots, and energy solutions [2] Chip Development - Tesla's chips are primarily designed for automotive applications, contrasting with Nvidia and AMD's GPUs that are aimed at general-purpose data centers [3] - The HW3 chip, introduced in 2019, operates at 72 TOPS per chip and 144 TOPS per board, optimized for low cost and power consumption in vehicles [4] - The HW4 chip, launched in 2023, offers 2x-4x better performance than HW3, utilizing Samsung's 7-nanometer technology for improved energy efficiency and thermal behavior [5] Application in Robotics - The same chip technology (HW3 and HW4) is applied in Tesla's humanoid robots, Optimus, enhancing their capabilities in vision perception, motion planning, and control [6]

Our children won’t learn to drive a car. ...

China’s https://t.co/GobvZ5M5lo plans to triple global robotaxi fleet by the end of 2026 https://t.co/hcvd7lWk52 ...

Zoox isn’t charging for rides in its purpose-built vehicles, which don’t have steering wheels, mirrors or pedals, just yet. But cofounder Jesse Levinson thinks a commercial waiver from regulators is close.Full story: https://t.co/xyPizaBGE8📸: Zoox https://t.co/17D5Kubd43 ...

Core Insights - Uber's stock price is currently around 91 dollars, reflecting a significant increase over the past year due to revenue growth and improved operating efficiency, despite volatility linked to tech-sector sentiment and regulatory changes [2][4] - The company achieved consistent profitability in late 2024, leading to a trailing P/E ratio of 11.69, the lowest since its IPO, while a forward P/E of 21.83 indicates expectations for continued earnings growth [2][4] - Analysts project Uber's stock could reach 184 dollars by 2030, with a consensus price target of 109.25 dollars, suggesting a potential upside of approximately 26 percent from current levels [5][7] Company Overview - Uber is transitioning from a ride-hailing service to a comprehensive mobility and logistics platform, with significant investments in technology and expansion in delivery and freight services [4][12] - The stock is favored by growth-oriented investors, but it remains in a "higher risk, higher reward" category due to regulatory, competitive, and macroeconomic factors [4][20] Financial Projections - For 2025, projections indicate cautious optimism, with expected stock prices ranging from a bullish prediction of 83.61 dollars to a bearish prediction of 69.89 dollars [8][16] - By 2030, bullish scenarios suggest Uber could solidify its dominance in multiple sectors, while bearish scenarios highlight risks from competition and regulatory challenges [19][20] Analyst Sentiment - A majority of analysts (29 out of 38) rate Uber as a Buy or Outperform, with the most optimistic forecasts reaching 150 dollars [7][12] - Recent analyst calls imply an average price target of 114.33 dollars, indicating a positive outlook for the stock [7] Growth Drivers - Sustained revenue growth and profitability across core segments, along with diversification into high-margin revenue streams such as autonomous vehicles and healthcare-related services, are key components of the bullish outlook [12][19] - International expansion in emerging markets is expected to enhance long-term growth prospects [12] Risks and Challenges - Regulatory risks, particularly around gig worker classification, could significantly impact costs and operational structure [13][14] - Competitive pressures from both traditional and new market entrants may limit market share and pricing power [13][14]

Core Insights - The article discusses the analysis of Uber's Q2 report and highlights the key takeaways from the report, maintaining a HOLD rating on the stock [1]. Group 1: Company Analysis - Uber's Q2 report was analyzed, focusing on the financial performance and operational metrics [1]. - The analysis indicates that the company is currently in a position where a HOLD rating is deemed appropriate, suggesting a cautious approach to investment in Uber [1]. Group 2: Analyst Background - The author is an independent investor with expertise in the Indian and US equity markets, holding a CFA Charter and a PhD in Finance from the University of Durham, U.K. [2]. - The author also serves as an Honorary Associate Professor in Finance and Corporate Governance at Brunel University London, indicating a strong academic background in finance [2]. - The author engages in quantitative research across various financial topics, including US equities and corporate governance, and has published in top-ranked peer-reviewed journals [2].

Core Points - Tesla has received approval to operate a ride-hailing service in Arizona, having met the requirements for a Transportation Network Company (TNC) permit as of November 17 [1][2] - The company has submitted a self-certification to test autonomous vehicles in Arizona, where regulations are less stringent compared to states like California [2] - Tesla's robotaxi service is currently operational in Austin and the San Francisco Bay Area, with plans to expand to eight to ten cities by the end of 2025 [4] Regulatory Requirements - In Arizona, companies must file a "Law Enforcement Interaction Plan" detailing emergency protocols and compliance with federal law [3] - The state requires a safety monitor to be present in the vehicle during testing, although it is unclear if Tesla will follow this requirement or adopt a different approach as seen in Austin [4] Service Expansion and User Experience - Tesla has expanded access to its app for all iOS users in the US and Canada, though it is uncertain if this expansion included an increase in fleet size [5] - Users have reported inconsistent wait times for the service, with instances of high demand affecting availability [5]

New global whitepaper explores the four forces transforming mobility over the next 10 years: alternative energy, autonomous vehicles, AI, and embedded access. From robotaxis to long-haul freight, autonomous vehicles could reduce operating costs by up to 57 per cent for trucking fleets while redefining urban transport economics.By 2035, AI and connectivity will handle 15 per cent of fleet work decisions autonomously, turning vehicles into intelligent, self-learning systems that operate like distributed netwo ...