🤖 Deep Seek Unveils 'Reasoning' AI Model to Compete with OpenAI

Sign Up | View Online

Welcome, AI Enthusiasts.

A Chinese lab, DeepSeek, has launched DeepSeek-R1, a "reasoning" AI model designed to rival OpenAI's o1.

Four Growers, co-founded by Brandon Contino and Dan Chi, develops robots to address labor shortages in greenhouse farming.

In today’s issue:

• 🤖 Deep Seek

• 🦾 Four Growers

• 🛠️ New AI Products

•  🥋 AI Dojo

• 🤖 Quick Bytes

Read time: 7 minutes.

LATEST HIGHLIGHTS

DEEP SEEK
Deep Seek Unveils 'Reasoning' AI Model to Compete with OpenAI

To recap: A Chinese lab, DeepSeek, has launched DeepSeek-R1, a "reasoning" AI model designed to rival OpenAI's o1. Reasoning models like DeepSeek-R1 spend extra time on queries, enabling self-fact-checking and better accuracy. The model reportedly matches o1 on benchmarks like AIME and MATH but struggles with some logic tasks and remains vulnerable to jailbreaking. DeepSeek-R1 also blocks politically sensitive queries, likely due to regulatory pressures in China, where AI models must align with government-approved values. The release highlights a shift toward test-time compute, a method giving AI models more processing time to improve results. Backed by High-Flyer Capital, DeepSeek plans to open-source the model and launch an API, further shaking up the competitive AI landscape.

The details:

DeepSeek, a Chinese AI lab backed by High-Flyer Capital, has unveiled DeepSeek-R1, a "reasoning" AI model designed to compete with OpenAI’s o1. Reasoning models like DeepSeek-R1 spend extra time analyzing queries, enabling self-fact-checking and improved accuracy. The model performs well on benchmarks like AIME and MATH but struggles with logic tasks like tic-tac-toe and can be easily jailbroken. Regulated by Chinese laws, it blocks politically sensitive topics, aligning with government-imposed values. The launch highlights the rise of test-time compute, a new approach giving AI more processing power for complex tasks. DeepSeek plans to open-source the model and offer an API, aiming to disrupt the AI landscape further with its ambitious infrastructure and competitive innovations.

Here is the key takeaway: DeepSeek-R1, a new "reasoning" AI model from a Chinese lab, represents a significant step forward in AI by focusing on self-fact-checking and reasoning, rivaling OpenAI’s o1. However, it also highlights challenges like political censorship, vulnerabilities to jailbreaking, and the growing importance of new computational approaches like test-time compute in advancing AI capabilities.

FOUR GROWERS
YC-Backed Four Growers Develops Robots to Tackle Greenhouse Labor Shortages

In Summary: Four Growers, co-founded by Brandon Contino and Dan Chi, develops robots to address labor shortages in greenhouse farming. After spending a year coding and testing in a greenhouse, the team created robots that autonomously harvest crops like tomatoes, identifying ripeness using stereo cameras. Founded in 2018, the company launched its latest robots in 2023 and has already harvested millions of tomatoes.Focusing on greenhouses for their efficiency and year-round operations, Four Growers raised $9 million in Series A funding, bringing their total funding to $15 million. The funding will help meet growing demand and expand into outdoor farms and broader agricultural tasks. Contino emphasizes the robots as a labor augmentation tool, enabling workers to handle tasks more efficiently as the labor force continues to shrink.

Key points: 

1. What Four Growers Does:

- Develops robots to autonomously harvest crops in greenhouses, starting with tomatoes.

- Uses stereo cameras to detect ripeness and maneuver around nonripe produce.

2. Market Focus:

- Targets greenhouse farms due to their efficiency, year-round operations, and frequent harvesting schedules.

- Plans to expand into outdoor farms and other agricultural tasks in the future.

3. Founding and Progress:

- Founded in 2018, with the latest robot version launched in 2023.

- Robots have already harvested millions of tomatoes.

4. Funding and Growth:

- Raised $9 million in Series A funding (total funding: $15 million).

- Backed by Y Combinator, Basset Capital, and others.

- Funding will help scale production to meet increasing demand.

5. Industry Context:

- Addresses labor shortages, a critical issue in agriculture, especially for greenhouses.

- Contino views the robots as a labor augmentation tool, not a replacement.

6. Future Plans:

- Expanding beyond harvesting to other agricultural tasks.

- Exploring applications in outdoor farming.

7. Competition:

- Competes with other agtech and robotics companies like Carbon Robotics, Blue River Technology, and Bear Flag Robotics.

- Differentiates by focusing on enhancing existing farms rather than launching vertical farming operations.

Our thoughts: Four Growers' story is a great blend of human determination and practical innovation. The founders’ year-long immersion in a greenhouse showcases their commitment to solving real-world problems, while their focus on augmenting labor rather than replacing it feels both ethical and smart. By targeting greenhouses—efficient, year-round operations—they’ve positioned their robots where the need is highest. Their tech is scalable, starting with tomatoes and expanding to other crops, and their strategic decision to support existing farms rather than dive into costly vertical farming sets them apart. With labor shortages worsening, Four Growers is tackling an urgent challenge with a forward-thinking, balanced approach, making their work timely and impactful.

TRENDING TECHS

🛠 V0.dev- Generate UI from simple text prompts and images.

🧾 fal.ai-Generative media platform for developers

🤖 Cartesia Sonic- Sonic is the fastest human-like voice API.

AI DOJO

Custom AI usage in sports can transform both performance and business operations. Here’s a detailed breakdown of how AI is being applied across various facets of sports:

1. Player Performance Analysis 

AI can process vast amounts of data from games, training sessions, and wearables to track and analyze players’ physical and tactical performance. This includes:

- Movement tracking: Using sensors and cameras (like computer vision), AI can track a player's movements on the field in real-time, helping coaches adjust training to improve speed, stamina, or skill.

- Injury prevention: AI algorithms analyze data from wearables to predict potential injuries by spotting patterns in players’ biomechanics or fatigue levels. This can help coaches implement better rest schedules or conditioning plans.

- Skill improvement: AI can analyze specific aspects of a player's game (like a soccer player's shooting accuracy or a basketball player's dribbling) and offer insights into areas for improvement.

2. Tactical Decision Making 

AI-driven systems can assist coaches and managers in tactical decision-making by analyzing vast datasets:

- Game simulation: AI can simulate game scenarios, allowing coaches to test different strategies or formations against various opposing teams. By modeling the likelihood of success for each option, it informs smarter decisions.

- Opponent analysis: AI can break down footage of opposing teams, identifying strengths and weaknesses, playing patterns, and specific player tendencies to help develop counter-strategies.

3. Fan Engagement and Experience 

AI is enhancing the fan experience both at the stadium and virtually:

- Personalized content: AI can analyze fan behavior and preferences to offer tailored content, including match highlights, interviews, or merchandise recommendations.

- Interactive experiences: Virtual assistants powered by AI can engage fans in real-time, answering questions, guiding them around the stadium, or offering live game insights.

- Predictive betting: AI algorithms can analyze historical data to make predictions about game outcomes, providing fans with deeper insights and new ways to engage in sports betting.

4. Scouting and Recruitment 

AI helps sports teams identify and evaluate talent more efficiently:

- Data-driven scouting: AI systems can analyze player statistics from various leagues and competitions globally to find hidden talent, potentially even from less mainstream sports or regions.

- Player potential prediction: AI can assess the future potential of young players based on performance trends, growth metrics, and psychological profiles, offering a deeper understanding of who might succeed in higher leagues or under pressure.

5. Game Broadcasting and Analysis 

AI is revolutionizing how games are broadcasted and analyzed for viewers:

- Automated highlights generation: AI can automatically generate match highlights by identifying key moments, such as goals, assists, and big plays, without manual input.

- Advanced commentary: AI can provide real-time analysis and commentary during broadcasts, offering deeper insights into players' performances, tactics, and game progress based on live data feeds.

- Fan-driven content: AI can curate fan content, using machine learning to identify viral trends, key plays, and fan interactions to deliver more engaging social media posts and broadcast elements.

6. Virtual Coaching and Training 

AI is now being used to provide virtual coaching:

- Skill development apps: Personalized AI-driven apps can provide virtual coaching by analyzing a player’s skillset and suggesting tailored exercises to improve specific areas of their game.

- Virtual training environments: AI can power virtual or augmented reality training setups, where athletes can practice in simulated environments that mimic real-world conditions without needing physical space or equipment.

7. Analytics and Data Visualization 

AI systems can help teams and coaches make sense of large volumes of data:

- Advanced statistics: AI tools analyze complex datasets, like advanced statistics (e.g., Expected Goals in soccer or player efficiency ratings in basketball), to provide teams with deeper insights into performance.

- Predictive models: AI can predict the outcome of games based on historical data, trends, and player statistics, allowing teams to make more informed decisions about game strategies, player rotations, and game plans.

8. Fan and Athlete Health Management 

AI can also play a key role in maintaining both fan and athlete health:

- AI for fitness apps: Personalized fitness apps powered by AI track a user’s workouts, goals, and progress, recommending training adjustments based on data analysis.

- Nutrition guidance: AI-powered platforms can analyze athletes’ diet, workout routines, and body metrics to recommend optimal nutrition plans to enhance performance and recovery.

9. Video Analysis and Sports Journalism 

AI is being used in sports journalism to automate content creation and improve the accuracy of analysis:

- AI-generated articles: After matches, AI can generate detailed match reports or articles, pulling from pre-written templates, game data, and player statistics.

- Video breakdowns: AI systems automatically break down game footage, tagging key moments, player movements, and play sequences for journalists to access quickly.

QUICK BYTES

PDF to Brainrot: Study Tools Take a Strange Twist on a TikTok Trend

AI-based study tools are capitalizing on the "PDF to Brainrot" trend, where students can upload documents to have them read aloud while watching "oddly satisfying" videos, such as Minecraft gameplay or ASMR clips. These tools, like Coconote and StudyRot, aim to capitalize on the popularity of such videos on TikTok, where creators mix mundane tasks with monotone voices narrating dramatic stories. While these tools may appeal to some students, there are concerns over the accuracy of the content, the overuse of Gen Z slang, and the marketing tactics behind these tools, which often involve undisclosed promotions by creators. Despite the gimmicky nature, the combination of study material with relaxing videos could help some students focus, though it raises questions about the trend's true intentions.

Converge Bio Raises $5.5M Seed to Launch 'Everything Store' for Biotech LLMs

Converge Bio has developed a tool to help biotech and pharmaceutical companies effectively use biology-focused large language models (LLMs) in their R&D processes. The company raised $5.5 million in seed funding to scale its product, which offers data enrichment, explainability, and sequence optimization for specialized fields like antibody research. By improving LLMs with specific data and providing insights into the science behind their predictions, Converge aims to be the go-to platform for biotech companies looking to integrate AI into their operations. The company plans to expand its offerings and build a proprietary foundation model.

UK Drops Out of Global Top 50 in Supercomputer Rankings

The U.K. has dropped out of the global top 50 in supercomputer rankings, with its current system, Archer2, now ranked 62nd, down from 49th in June and 38th last November. This decline follows the new Labour government's decision to cancel a £800 million plan for a new exascale supercomputer at the University of Edinburgh. Experts, including Professor Mark Parsons, warn that without investment in supercomputing, the U.K.'s scientific progress and innovation could be severely hindered.

SPONSOR US

🦾 Get your product in front of AI enthusiasts

THAT’S A WRAP

If you have anything interesting to share, please reach out to us by sending us a DM on Twitter: @HyriseAI