PH Deck

Users struggle with complex reasoning tasks, especially in math, using existing language models.

Drawbacks: Existing models may lack computational efficiency and optimization for size.

Users currently rely on older, less efficient machine learning models that may not offer optimal performance for specific applications. Users experience difficulties with obtaining high-performance outputs and adapting models for specialized tasks.

Users exploring the capabilities of Large Language Models (LLMs) often face difficulty in coming up with effective prompts to fully leverage these models' potential. This leads to suboptimal usage and experimentation, hindering learning and application in various contexts. The drawbacks include a lack of inspiration, inefficiencies in understanding the full capabilities of LLMs, and an inability to apply these models effectively across different domains.

Users struggle with traditional AI models that lack the ability to perform complex reasoning and provide long chains of thought before responding.

Teams experience challenges in collaborating effectively across different tools and devices, leading to fragmented workflow and decreased productivity. The difficulties in seamless co-creation and task management across various platforms pose significant drawbacks.

In the current situation, the user faces limitations in traditional computing where solving complex problems like discovering new medicines or designing revolutionary materials is computationally intensive and time-consuming. The drawback is the inability to efficiently process and analyze vast amounts of data necessary for making breakthrough decisions. Users face challenges in leveraging traditional chip architectures to address these complex computational problems. The existing solutions do not allow for scaling up computations using qubits effectively, which stifles innovation and complex problem-solving capabilities.

Users seeking to learn new languages often find existing platforms and apps overwhelming due to excessive gamification and cluttered interfaces, which can detract from effective learning.

Learning a new language can be challenging and time-consuming, often limited by the availability of tutors and suitable learning environments. The traditional methods require learners to adapt to specific class schedules, which may not fit into everyone's busy lives. Additionally, the cost of hiring personal tutors or enrolling in language courses can be prohibitive for many. The limited availability of tutors and high costs are significant drawbacks in the traditional language learning process.

In the current situation, users are facing limitations in AI-based tools as they struggle with less effective coding assistance, limited reasoning capabilities, and inability to handle complex prompts effectively.

Less effective coding assistance, limited reasoning capabilities, and inability to handle complex prompts effectively are the drawbacks of the old situation.

Designers, brands, and e-commerce businesses struggle with creating lifelike digital fashion models for showcasing clothing and designs.