Get ready for a deep dive into the massive shifts expected in U.S. online shopping this holiday season! We analyze a new report from Adobe Analytics, drawing predictions from over 1 trillion visits to U.S. retail sites.

The E-Commerce Forecast:The total U.S. holiday shopping season is expected to generate $253.4 billion in online sales, representing a 5.3% year-over-year increase. We break down the key shopping days, where Cyber Monday is forecasted to remain the biggest day, reaching $14.2 billion. Black Friday is expected to hit $11.7 billion, and consumers are expected to spend $6.4 billion online even on Thanksgiving Day.

The AI Explosion:The centerpiece of this season is the overwhelming growth of generative AI-powered shopping. Adobe predicts that AI traffic will skyrocket by 520% year-over-year, peaking in the 10 days leading up to Thanksgiving. This follows a tremendous 1,300% increase in AI traffic seen during the previous year. Learn how consumers plan to leverage this technology:

• 53% of surveyed consumers plan to use AI services for research ahead of purchases.
• 40% expect to use AI for product recommendations.
• Other common uses include deal finding (36%) and gift inspiration (30%).

AI usage is anticipated to be highest across categories like toys, electronics, jewelry, and personal care.

Beyond AI: Key Trends Driving Sales:We explore the other major trends shaping consumer behavior and spending:

1. Mobile Dominance: Mobile devices are set to drive more online spend than desktop shopping, reaching a record 56.1% share of transactions.
2. Buy Now, Pay Later (BNPL): BNPL services are poised for significant growth, expected to drive $20.2 billion in online spend, an 11% increase year-over-year. Cyber Monday alone is expected to hit a BNPL milestone of $1.04 billion.
3. Discounts and Advertising: Consumer demand for discounts is strong, with products expected to be 28% off listed prices. Furthermore, social media advertising is expected to drive a 51% year-over-year increase in online revenue.

Finally, we look at the top categories for overall spending, including electronics ($57.5 billion), apparel ($47.6 billion), and furniture ($31.1 billion). Tune in to understand the complex forces defining the future of e-commerce.

This episode dives into the massive partnership between AMD and OpenAI, a move specifically designed to challenge Nvidia’s dominance in the AI chip market.

We explore the details of this five-year agreement, which commits OpenAI to purchasing six gigawatts worth of AMD’s GPUs for its burgeoning AI data centers. This infrastructure bolster is crucial for meeting the growing computational demands required for applications such as ChatGPT.

The deal is expected to deliver “tens of billions of dollars in revenue” for AMD. Following the announcement, the company’s stock price increased by 24 percent in pre-market trading. Deployment is scheduled to begin in the second half of 2026, starting with a gigawatt deployment of AMD Instinct MI450 GPUs.

AMD CEO Lisa Su expressed excitement about the partnership, stating that it brings the best of both companies together to enable the world’s most ambitious AI buildout and advance the entire AI ecosystem. OpenAI CEO Sam Altman echoed this sentiment, calling it a major step toward building the compute capacity needed to realize AI’s full potential, noting that AMD’s leadership will accelerate progress.

We also analyze the strategic positioning of this agreement relative to OpenAI's existing plans. While OpenAI previously established Nvidia as a “preferred strategic compute and networking partner,” AMD is defined as a “core strategic compute partner”. Furthermore, the deal offers a significant incentive: OpenAI has the option to receive up to 160 million AMD shares—approximately a ten percent stake—at a cent per share, dependent on achieving specific milestones.

Join us as we discuss how this critical partnership is disrupting the semiconductor landscape and shaping the future of AI infrastructure.

The European Union is launching its ambitious “Apply AI strategy,” a comprehensive plan designed to secure digital sovereignty and significantly reduce the bloc’s technological reliance on foreign providers, particularly the US and China. This initiative seeks to strengthen “EU AI sovereignty” by accelerating the development and use of homemade artificial intelligence technologies.

The strategy emphasizes positioning AI not just as a productivity tool, but as a “strategic asset” that must be tightly integrated across the EU’s institutional, industrial, and security systems.

A core justification for this shift is the warning that “external dependencies of the AI stack”—referring to the underlying software and infrastructure needed to build and train AI applications— “can be weaponised” by state and non-state actors, thereby posing a risk to critical supply chains. Concerns regarding Europe’s reliance on American technology have increased, especially following Donald Trump’s return to the US presidency.

To execute the strategy's goals, the European Commission is mobilizing €1 billion from existing financing programs. The strategy highlights the need to improve AI usage and adoption across vital sectors, including manufacturing, healthcare, and defence.

Crucially, the EU is prioritizing the implementation of European AI-enabled tools in its defence systems, reacting to the threat from Russia and fears of potential US disengagement from European security. This includes plans to accelerate the development and deployment of European AI-enabled command and control (C2) capacities. C2 systems are critical enablers used for instructing troops and managing battlefield operations, areas where European militaries currently rely heavily on the US through Nato. The commission is also pushing for the development of sovereign frontier models specifically for space defence technology.

Although Europe hosts promising AI companies, such as the French model maker Mistral and the German defence tech group Helsing, the EU currently remains dependent on the US and Asia for the necessary hardware, software, and critical minerals needed for AI development. The strategy aims to mitigate this reliance by having public administrations play a central role in stimulating demand for European-made open source AI solutions, helping start-ups to grow. European Commission president Ursula von der Leyen stated the goal is to “speed up AI adoption across the board” to ensure Europe does not miss out on this revolutionary technology.

This podcast centers on a secret device being developed collaboratively by OpenAI and renowned designer Jony Ive. This device is the first in a family of devices being developed by Ive and OpenAI CEO Sam Altman, and it is currently targeted for release sometime in late 2026 or early 2027.

The core ambition for this AI gadget is to provide an AI-assistant experience similar to Apple’s digital voice assistant Siri, but with the goal of making it "better".

The concept guiding the development is that the user should have "a friend who’s a computer who isn’t your weird AI girlfriend," according to one source briefed on the plans.

Key physical details reported about the device include:

• It is described as being palm-sized.
• It is roughly the size of a smartphone.
• It lacks a screen.
• It can be carried around by the user or placed on surfaces like a desk or table.
• It is designed to communicate with users using a microphone, speaker, and camera, or potentially multiple cameras.

OpenAI is seeking ways to ensure the gadget is "accessible but not intrusive". The approach being considered is an "always on" methodology that continuously gathers data throughout the day, differing from devices like Amazon’s Alexa-powered Echo devices which are activated by specific verbal prompts.

OpenAI and Ive are trying to solve a number of technical challenges before the mysterious AI gadget can be released. The company is reportedly struggling to perfect the AI-gadget’s voice and personality.

The main hurdles include:

1. Personality and Engagement: Struggling to decide on the voice and mannerisms for the AI-powered device. This includes figuring out the device’s "personality" and how often it should engage with users and finish a conversation.
2. Privacy Concerns: Overcoming privacy issues related to the device’s "always-listening" nature.
3. Computing Infrastructure: Budgeting constraints for computing infrastructure must be overcome. Sources indicate that OpenAI is struggling to get enough compute resources for ChatGPT, let alone for a new dedicated AI device, suggesting this needs to be fixed first.

Dive into the details of the evolving policies surrounding OpenAI’s new video app, Sora. Despite being an invite-only platform, Sora rapidly climbed to the top of the App Store charts. The app's distinctive features include "cameos," which allow users to upload their biometric data so their digital likeness can be featured in AI-generated videos.

However, the excitement around Sora has been matched by controversy, particularly concerning intellectual property. Users have demonstrated a delight in flouting copyright laws by creating videos that utilize popular, studio-owned characters. Examples include users generating content where characters like Pikachu and SpongeBob interact with deepfakes of OpenAI CEO Sam Altman, sometimes even criticizing the company's approach to copyright.

In response to these issues, OpenAI appears to be reversing its course on copyright. Previously, reports suggested OpenAI required Hollywood studios and agencies to explicitly opt out if they wished their IP to be excluded from Sora-generated videos. Now, CEO Sam Altman has announced two critical planned changes.

First, the company is implementing "more granular control over generation of characters". The key shift here is moving to an "opt-in" model. This suggests that users will be prevented from creating videos featuring copyrighted characters unless rightsholders have given Sora explicit permission to do so. Altman noted that many rightsholders are excited about the potential for this "interactive fan fiction" but require the ability to specify exactly how their characters can be used—including the option to block usage entirely. Despite this new approach, Altman acknowledged that there are likely to be "some edge cases of generations that get through that shouldn’t".

Second, the company is planning an unspecified form of video monetization. While the previous plan was only to charge users for creating extra videos during periods of high demand, Altman elaborated on this by suggesting that revenue generated could be shared with rightsholders. Ultimately, OpenAI hopes the new kind of engagement created through Sora is even more valuable than the revenue share, but the goal is for both the engagement and the revenue share to be valuable. Tune in as we discuss these sweeping changes affecting AI, media, and intellectual property.

The digital threat landscape is evolving rapidly, forcing companies to make AI phishing detection a top priority for 2026. Traditional signature-based defenses are insufficient and no match for the sheer scale and sophistication of modern campaigns.

Discover how artificial intelligence is transforming cybercrime, making phishing faster, cheaper, and more effective. Researchers used popular AI chatbots like Grok and ChatGPT to craft the "perfect phishing email" using a simple prompt, demonstrating the power of these tools. This experiment showed that 11% of volunteers clicked on the malicious links generated by the AI. These sophisticated emails are no longer generic spam; generative AI tools create personalized messages by scraping data from sources like LinkedIn, mirroring real business context to entice even the most careful employees.

The threat environment is worsened by the emergence of Phishing-as-a-Service (PhaaS) platforms on the dark web, such as Lighthouse and Lucid. These subscription-based kits allow low-skilled criminals to launch highly sophisticated campaigns. The ease of entry means criminals can spin up cloned login portals for major services like Google, Okta, or Microsoft that look virtually identical to the real sites in just 30 seconds. The technology is also fueling a massive surge in deepfake audio and video phishing, which has increased by 1,000% over the past decade. Criminals often impersonate trusted figures, like CEOs, family members, or colleagues, over communication channels such as Zoom, WhatsApp, and Teams.

We explore the essential, multi-layered strategies needed to combat this perfect AI storm. Learn how Natural Language Processing (NLP) models can provide better threat analysis than static filters. These models are trained on legitimate communication patterns to catch subtle deviations in structure, phrasing, or tone that a trained human might miss. Since it is very likely that some AI phishing emails will still find their way to the inbox, having a well-trained workforce is necessary for detection. We detail how simulation-based training is the most effective approach, preparing employees for the exact type of attacks they are most likely to face and building the "muscle memory" required to report suspicious activity naturally.

Finally, we examine the crucial role of User and Entity Behaviour Analytics (UEBA). This final layer of defense ensures that a successful phishing attempt does not result in a full-scale compromise by detecting unusual user or system activities, such as a login from an unexpected location or unusual mailbox changes.

Ultimately, success in cybersecurity heading into 2026 will depend on combining advanced technology with human readiness. Tune in to understand why continuous monitoring, AI-driven detection, and realistic simulation training are non-negotiable priorities.

Agriculture is a remarkably thirsty industry, consuming 70% of all fresh water used worldwide. In many countries, such as Chile or India, this consumption can be even higher, sometimes exceeding 90%, making the lack of water a critical local and global issue.

In this episode, we explore Instacrops, a startup founded by Mario Bustamante, that is betting that artificial intelligence can dramatically slash water use on farms. Instacrops originally focused on deploying internet-of-things (IoT) sensors to warn farmers about frost, but it pivoted to specialized software and water use as hardware became commoditized.

The Instacrops system processes massive amounts of data, handling roughly 15 million data points per hour. Their LLM models ingest more than 80 parameters, including soil moisture, humidity, temperature, pressure, crop yield, and NDVI, a plant productivity metric derived from satellite imagery.

The results are substantial: Instacrops is currently helping 260 farms. They have helped these farms cut water use by up to 30% while also increasing crop yields by as much as 20%.

This shift allows the company to generate more impact with less cost and fewer team members.Farmers receive advisories directly on their mobile phones. While Instacrops offers a chatbot app, the founder expects they will soon be 100% integrated with WhatsApp, which is seen as a universal tool for farmers. On more technologically advanced farms, Instacrops can directly control irrigation systems.

The company focuses on high-value crops in Latin America, such as apples, avocados, blueberries, almonds, and cherries. To gain access to these crucial irrigation insights, farmers pay an annual fee based on the hectare of farmland they utilize.

Instacrops is generating buzz as part of Startup Battlefield and will be presenting their technology at TechCrunch Disrupt in San Francisco.

In this episode, we discuss how a Reuters article reports on the removal of numerous AI-generated Bollywood videos from YouTube following a news story that highlighted their similarity to content involved in a significant legal challenge.

Specifically, celebrity couple Abhishek Bachchan and Aishwarya Rai Bachchan filed a lawsuit seeking to protect their intellectual property rights and challenge YouTube’s AI training policies regarding unauthorized content.

After Reuters' reporting, hundreds of AI-manipulated videos, many sexually explicit or misleading, were deleted, including content from a popular channel with millions of views that featured AI depictions of celebrities kissing or romancing.

While YouTube stated the channel was removed by its creator and that the company prohibits doctored and misleading content, other similar infringing videos remained accessible even after the purge.

This situation underscores the ongoing tension between AI manipulation, celebrity rights, and platform responsibility in one of YouTube's largest global markets, India.

In the nearly three years since ChatGPT launched, chatbots have been the primary way most people experience generative AI. But that's all about to change. We are now entering a new period of experimentation in AI apps, as companies like OpenAI search for the next "killer apps" to put their powerful and expensive AI models to work.

Join us as we explore the central question of this new era: Will AI lead to a generation of brand-new applications built from the ground up, or will most people experience it simply as new features added to the apps they already use?

In This Episode, We Discuss:

• The New Frontier in Social Media: An early test for new AI apps appears to be in short-form video. We break down OpenAI's new social network, Sora, which lets you insert yourself and friends into AI-generated videos . OpenAI has declared its ambition for Sora to be the “GPT-3.5 moment for video”. This comes as YouTube adds AI features and Meta launches its own feed of AI-generated videos.
• Reclaiming the Social Graph: OpenAI claims its video app will foster new community behaviors, a direct challenge to platforms like Meta, which has been moving away from content from friends in its feeds. But we ask if the novelty of running around an imagined landscape with a friend can lead to lasting changes in social interaction.
• Proactive and Unprompted AI: We look beyond video to other experiments, such as OpenAI's ChatGPT Pulse, which tries to anticipate your information needs and deliver a selection of useful information once a day, unprompted.
• The Billion-Dollar Question — Monetization: How will these new AI apps make money? We examine OpenAI's promise that it is “not optimizing for time spent in feed” and its plan to charge users for creating extra videos. CEO Sam Altman has expressed deep discomfort with advertising, echoing the Google founders' original 1998 position. However, we question if OpenAI can resist the pressure to adopt ad-based models to finance its massive spending plans and compete with giants like Google and Meta.

Tune in to understand the strategies, innovations, and challenges shaping the future of your digital life.

Is generative AI a revolutionary learning assistant or "the height of self-sabotage"? On this episode of The Daily AI Chat, we explore the academic front lines where computer science professors are grappling with the impact of tools like ChatGPT on education.

Since the launch of these powerful AI models, some Yale instructors report that students are showing a diminished understanding of foundational concepts. They argue that using AI to complete assignments prevents students from developing crucial problem-solving and critical thinking skills—the very abilities they are there to learn. One professor compares learning to code to training for a marathon: there's no substitute for "just running some miles".

In response, many are making drastic changes. We dive into how faculty are restructuring their courses, with some dropping the grade weight of homework to zero and making in-person exams worth as much as 90% of the final grade. The goal? To remove the incentive to use AI for assignments and force students to truly master the material.But not everyone sees AI as the enemy. We also look at the educators who are constructively integrating AI into their classrooms. From courses that encourage students to use AI as a "coworker" for coding assistance to professors who liken it to a "smart older sister who could help you study for a test", some are finding innovative ways to leverage these tools.

Tune in to hear how professors are navigating this new reality, from designing AI-proof homework to embracing AI as a collaborator, all while operating with "wide latitude" from the university to set their own classroom policies.