Refined social media strategy forged through leading Amazon’s global programs.
What I Believe
Your social media presence is the alignment of voice, visuals, and vision — elevated to create influence that endures. I believe in building presence that feels as natural as it is refined, and as undeniable as the future you’re shaping.
Work With Me
Presence
Architecture
Content
Craft
Rollout
Guidance
Get to Know Me
With over 10 years of experience leading digital content programs for brands like Prime Video, Amazon Business, and Veloz, my work focuses on three things:
This site is part portfolio, part resource, and part open door. Whether you’re laying the groundwork for a social presence or preparing to launch at scale, I’m glad you found your way here.
I collaborate with a trusted network of creatives and strategists who scale up or down depending on what the work calls for, always bringing the right energy, clarity, and direction.
If you’re values-driven, impact-oriented, and navigating growth or change, we’ll probably get along.
Feel free to connect with me on LinkedIn. I’d love to hear what you’re building.
Your partner in purpose,
Tess Smith
Entrepreneurs, educators, & advocates driving social or cultural impact.
Change Management
Emotional Intelligence
Change-makers are the ones redefining what’s possible, redirecting the master narrative, and protecting communities.
I’m here to help you transform bold ideas into sustainable impact.
I thrive at the intersection of emotional intelligence and empathy-driven change management, helping you navigate the complexities of transformation with care and clarity.
Whatever you’re working toward, I would be honored to amplify the movement.
Artists, filmmakers, writers, & designers looking to scale their vision.
Strategy
Analytics
Marketing Yourself
…these things tend to give even the most successful creators a case of the spookies.
Let us translate your genius and back it up with data and narrative.
We’re the team you call when the creative sparks fly but the details start to weigh you down.
From capturing those behind-the-scenes moments to brainstorming bold ideas or locking in the opportunities that take you to the next level, we’ve got you covered.
Nonprofits, start-ups, mission-focused brands, & socially responsible companies.
Whether you need:
a creative partner
a strategist
an executor
all of the above
—I’m here for it.
I’ve worked with professionals at every level, from C-suites and executive directors to board members, strategists, managers, and individual contributors, making sure everyone understands their role and feels empowered to contribute to the project’s greater purpose.
Thank you for taking the time to explore my portfolio.
Every project here represents a relationship built on trust—trust from mission-driven organizations and individuals with big ideas and the courage to pursue them.
That trust is something I deeply respect.
Each campaign I’ve created, every strategy I’ve designed, and all the content I’ve crafted have been opportunities to amplify voices that matter, highlight meaningful work, and connect people through shared purpose.
For me, marketing isn’t about selling—it’s about serving. It’s about showing up with creativity, clarity, and commitment to help others bring their vision to life.
Thank you for being here. I hope my work inspires you to imagine what’s possible for your own purpose, and I look forward to the possibility of supporting your journey.
With gratitude,
Tess
What is Federated Learning?
Federated learning is an AI training approach that enhances privacy and security by keeping data localized on users’ devices instead of centralizing it in one location. This decentralized method allows models to learn from data across multiple devices or servers while only sharing insights—rather than raw data—back to a central system.
In the context of AI responsibility, federated learning minimizes data exposure, reduces the risk of breaches, and supports compliance with data protection regulations like GDPR and CCPA. It also promotes ethical AI development by preserving user control over personal information and enabling more inclusive and privacy-focused AI systems.
What is Dynamic Workload Scheduling?
Dynamic workload scheduling is an energy-efficient computing strategy that adjusts when and where AI workloads are processed based on real-time conditions, such as renewable energy availability, electricity prices, and server capacity.
In the context of sustainable AI computing, it means shifting AI training or inference tasks to times and locations where renewable energy sources (like solar and wind) are abundant to reduce carbon emissions and energy costs.
How Does Dynamic Workload Scheduling Work?
Aligning AI Training with Renewable Energy Peaks
Load Balancing Across Data Centers
Taking Advantage of Variable Electricity Pricing
AI-Optimized Scheduling Systems
Google’s Carbon-Aware Computing:
Microsoft’s Project Forge Global Scheduler:
What Is an AI Accelerator?
An AI accelerator is a specialized hardware component designed to speed up artificial intelligence (AI) and machine learning (ML) workloads more efficiently than traditional processors like CPUs (Central Processing Units) or even GPUs (Graphics Processing Units). These accelerators are optimized for parallel processing, lower energy consumption, and high-performance AI computations.
How Do AI Accelerators Work?
Unlike general-purpose CPUs, which handle a wide variety of computing tasks, AI accelerators are custom-built for specific AI operations such as:
Matrix multiplications & tensor processing (core operations in deep learning).
Neural network training & inference (faster model execution).
Optimized data flow (reducing memory bottlenecks).
These accelerators reduce the energy and time required to train AI models and process real-time AI applications, making them crucial for sustainable computing strategies.
Examples of AI Accelerators
1. Google Tensor Processing Units (TPUs)
What it is: Custom-built by Google for deep learning workloads.
Why it matters: Uses less power than GPUs while accelerating AI model training.
Example: Google’s TPUs power Google Search, Google Photos, and AI-driven healthcare research.
2. AWS Inferentia (Amazon Web Services)
What it is: A custom AI chip designed for machine learning inference (running trained AI models efficiently).
Why it matters: Uses lower power and costs less than GPUs for AI-powered applications.
Example: Powers Alexa, AWS AI services, and real-time recommendations for e-commerce.
3. NVIDIA Grace Hopper Superchip
What it is: A hybrid CPU-GPU superchip designed for high-performance AI applications.
Why it matters: Reduces energy consumption while handling massive AI models like large language models (LLMs).
Example: Used in supercomputers, autonomous vehicles, and generative AI models.
A specialized processor designed for parallel processing, originally developed for rendering graphics. GPUs have thousands of smaller cores that can process multiple tasks simultaneously, making them ideal for AI, machine learning, gaming, and high-performance computing. Unlike CPUs, GPUs are optimized for large-scale data computations, enabling faster processing of complex mathematical operations.
