In this tutorial, we’ll build an end‑to‑end ticketing assistant powered by Agentic AI using the PydanticAI library. We’ll define our data rules with Pydantic v2 models, store tickets in an in‑memory SQLite database, and generate unique identifiers with Python’s uuid module. Behind the scenes, two agents, one for creating tickets and one for checking status, leverage Google Gemini (via PydanticAI’s google-gla provider) to interpret your natural‑language prompts and call our custom database functions. The result is a clean, type‑safe workflow you can run immediately in Colab. !pip install --upgrade pip !pip install pydantic-ai First, these two commands update your pip installer to the latest version, bringing in new features and security patches, and then install PydanticAI. This library enables the definition of type-safe AI agents and the integration of Pydantic models with LLMs. import os from getpass import getpass if "GEMINI_API_KEY" not in os.environ: os.environ["GEMINI_API_KEY"] = getpass("Enter your Google Gemini API key: ") We check whether the GEMINI_API_KEY environment variable is already set. If not, we securely prompt you (without echoing) to enter your Google Gemini API key at runtime, then store it in os.environ so that your Agentic AI calls can authenticate automatically. !pip install nest_asyncio We install the nest_asyncio package, which lets you patch the existing asyncio event loop so that you can call async functions (or use .run_sync()) inside environments like Colab without running into “event loop already running” errors. import sqlite3 import uuid from dataclasses import dataclass from typing import Literal from pydantic import BaseModel, Field from pydantic_ai import Agent, RunContext We bring in Python’s sqlite3 for our in‑memory database and uuid to generate unique ticket IDs, use dataclass and Literal for clear dependency and type definitions, and load Pydantic’s BaseModel/​Field for enforcing data schemas alongside Agent and RunContext from PydanticAI to wire up and run our conversational agents. conn = sqlite3.connect(":memory:") conn.execute(""" CREATE TABLE tickets ( ticket_id TEXT PRIMARY KEY, summary TEXT NOT NULL, severity TEXT NOT NULL, department TEXT NOT NULL, status TEXT NOT NULL ) """) conn.commit() We set up an in‑memory SQLite database and define a tickets table with columns for ticket_id, summary, severity, department, and status, then commit the schema so you have a lightweight, transient store for managing your ticket records. @dataclass class TicketingDependencies: """Carries our DB connection into system prompts and tools.""" db: sqlite3.Connection class CreateTicketOutput(BaseModel): ticket_id: str = Field(..., description="Unique ticket identifier") summary: str = Field(..., description="Text summary of the issue") severity: Literal["low","medium","high"] = Field(..., description="Urgency level") department: str = Field(..., description="Responsible department") status: Literal["open"] = Field("open", description="Initial ticket status") class TicketStatusOutput(BaseModel): ticket_id: str = Field(..., description="Unique ticket identifier") status: Literal["open","in_progress","resolved"] = Field(..., description="Current ticket status") Here, we define a simple TicketingDependencies dataclass to pass our SQLite connection into each agent call, and then declare two Pydantic models: CreateTicketOutput (with fields for ticket ID, summary, severity, department, and default status “open”) and TicketStatusOutput (with ticket ID and its current status). These models enforce a clear, validated structure on everything our agents return, ensuring you always receive well-formed data. create_agent = Agent( "google-gla:gemini-2.0-flash", deps_type=TicketingDependencies, output_type=CreateTicketOutput, system_prompt="You are a ticketing assistant. Use the `create_ticket` tool to log new issues." ) @create_agent.tool async def create_ticket( ctx: RunContext[TicketingDependencies], summary: str, severity: Literal["low","medium","high"], department: str ) -> CreateTicketOutput: """ Logs a new ticket in the database. """ tid = str(uuid.uuid4()) ctx.deps.db.execute( "INSERT INTO tickets VALUES (?,?,?,?,?)", (tid, summary, severity, department, "open") ) ctx.deps.db.commit() return CreateTicketOutput( ticket_id=tid, summary=summary, severity=severity, department=department, status="open" ) We create a PydanticAI Agent named’ create_agent’ that’s wired to Google Gemini and is aware of our SQLite connection (deps_type=TicketingDependencies) and output schema (CreateTicketOutput). The @create_agent.tool decorator then registers an async create_ticket function, which generates a UUID, inserts a new row into the tickets table, and returns a validated CreateTicketOutput object. status_agent = Agent( "google-gla:gemini-2.0-flash", deps_type=TicketingDependencies, output_type=TicketStatusOutput, system_prompt="You are a ticketing assistant. Use the `get_ticket_status` tool to retrieve current status." ) @status_agent.tool async def get_ticket_status( ctx: RunContext[TicketingDependencies], ticket_id: str ) -> TicketStatusOutput: """ Fetches the ticket status from the database. """ cur = ctx.deps.db.execute( "SELECT status FROM tickets WHERE ticket_id = ?", (ticket_id,) ) row = cur.fetchone() if not row: raise ValueError(f"No ticket found for ID {ticket_id!r}") return TicketStatusOutput(ticket_id=ticket_id, status=row[0]) We set up a second PydanticAI Agent, status_agent, also using the Google Gemini provider and our shared TicketingDependencies. It registers an async get_ticket_status tool that looks up a given ticket_id in the SQLite database and returns a validated TicketStatusOutput, or raises an error if the ticket isn’t found. deps = TicketingDependencies(db=conn) create_result = await create_agent.run( "My printer on 3rd floor shows a paper jam error.", deps=deps ) print("Created Ticket →") print(create_result.output.model_dump_json(indent=2)) tid = create_result.output.ticket_id status_result = await status_agent.run( f"What's the status of ticket {tid}?", deps=deps ) print("Ticket Status →") print(status_result.output.model_dump_json(indent=2)) Finally, we first package your SQLite connection into deps, then ask the create_agent to log a new ticket via a natural‑language prompt, printing the validated ticket data as JSON. It then takes the returned ticket_id, queries the status_agent for that ticket’s current state, and prints the status in JSON form. In conclusion, you have seen how Agentic AI and PydanticAI work together to automate a complete service process, from logging a new issue to retrieving its live status, all managed through conversational prompts. Our use of Pydantic v2 ensures every ticket matches the schema you define, while SQLite provides a lightweight backend that’s easy to replace with any database. With these tools in place, you can expand the assistant, adding new agent functions, integrating other AI models like openai:gpt-4o, or connecting real‑world APIs, confident that your data remains structured and reliable throughout. Here is the Colab Notebook. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Group. Don’t Forget to join our 90k+ ML SubReddit. Asif RazzaqWebsite |  + postsBioAsif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.Asif Razzaqhttps://www.marktechpost.com/author/6flvq/Atla AI Introduces the Atla MCP Server: A Local Interface of Purpose-Built LLM Judges via Model Context Protocol (MCP)Asif Razzaqhttps://www.marktechpost.com/author/6flvq/Long-Context Multimodal Understanding No Longer Requires Massive Models: NVIDIA AI Introduces Eagle 2.5, a Generalist Vision-Language Model that Matches GPT-4o on Video Tasks Using Just 8B ParametersAsif Razzaqhttps://www.marktechpost.com/author/6flvq/Serverless MCP Brings AI-Assisted Debugging to AWS Workflows Within Modern IDEsAsif Razzaqhttps://www.marktechpost.com/author/6flvq/A Step-by-Step Coding Guide to Defining Custom Model Context Protocol (MCP) Server and Client Tools with FastMCP and Integrating Them into Google Gemini 2.0’s Function‑Calling Workflow

Designing intelligent systems that function reliably in dynamic physical environments remains one of the more difficult frontiers in AI. While significant advances have been made in perception and planning within simulated or controlled contexts, the real world is noisy, unpredictable, and resistant to abstraction. Traditional AI systems often rely on high-level representations detached from their physical implementations, leading to inefficiencies in response time, brittleness to unexpected changes, and excessive power consumption. In contrast, humans and animals exhibit remarkable adaptability through tight sensorimotor feedback loops. Reproducing even a fraction of that adaptability in embodied systems is a substantial challenge. Physical Intelligence Introduces π-0.5: A Framework for Embodied Adaptation To address these constraints, Physical Intelligence has introduced π-0.5—a lightweight and modular framework designed to integrate perception, control, and learning directly within physical systems. As described in their recent blog post, π-0.5 serves as a foundational building block for what the team terms “physical intelligence”: systems that learn from and adapt to the physical world through constant interaction, not abstraction alone. Rather than isolating intelligence in a centralized digital core, π-0.5 distributes processing and control throughout the system in compact modules. Each module, termed a “π-node,” encapsulates sensor inputs, local actuation logic, and a small, trainable neural component. These nodes can be chained or scaled across various embodiments, from wearables to autonomous agents, and are designed to react locally before resorting to higher-level computation. This architecture reflects a core assumption of the Physical Intelligence team: cognition emerges from action—not apart from it. Technical Composition and Functional Characteristics π-0.5 combines three core elements: (1) low-latency signal processing, (2) real-time learning loops, and (3) modular hardware-software co-design. Signal processing at the π-node level is tailored to the physical embodiment—allowing for motion-specific or material-specific response strategies. Learning is handled through a minimal but effective reinforcement update rule, enabling nodes to adapt weights in response to performance signals over time. Importantly, this learning is localized: individual modules do not require centralized orchestration to evolve their behavior. A central advantage of this decentralized model is energy efficiency. By distributing computation and minimizing the need for global communication, the system reduces latency and energy draw—key factors for edge devices and embedded systems. Additionally, the modularity of π-0.5 makes it hardware-agnostic, capable of interfacing with a variety of microcontrollers, sensors, and actuators. Another technical innovation is the system’s support for tactile and kinesthetic feedback integration. π-0.5 is built to accommodate proprioceptive sensing, which enhances its capacity to maintain adaptive behavior in response to physical stress, deformation, or external forces—especially relevant for soft robotics and wearable interfaces. Preliminary Results and Application Scenarios Initial demonstrations of π-0.5 showcase its adaptability across a variety of scenarios. In a soft robotic gripper prototype, the inclusion of π-0.5 nodes enabled the system to self-correct grip force based on the texture and compliance of held objects—without relying on pre-programmed models or external computation. Compared to a traditional control loop, this approach yielded a 30% improvement in grip accuracy and a 25% reduction in power consumption under similar test conditions. In wearable prototypes, π-0.5 allowed for localized adaptation to different body movements, achieving smoother haptic feedback and better energy regulation during continuous use. These results highlight π-0.5’s potential not just in robotics but in augmentative human-machine interfaces, where context-sensitive responsiveness is critical. Conclusion π-0.5 marks a deliberate step away from monolithic AI architectures toward systems that closely couple intelligence with physical interaction. Rather than pursuing ever-larger centralized models, Physical Intelligence proposes a distributed, embodied approach grounded in modular design and real-time adaptation. This direction aligns with long-standing goals in cybernetics and biologically inspired computing—treating intelligence not as a product of abstraction, but as a property that emerges from constant physical engagement. As AI continues to move into real-world systems, from wearables to autonomous machines, the need for low-power, adaptive, and resilient architectures will grow. π-0.5 offers a compelling foundation for meeting these requirements, contributing to a more integrated and physically grounded conception of intelligent systems. Check out the Technical details. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Group. Don’t Forget to join our 90k+ ML SubReddit. NikhilNikhil is an intern consultant at Marktechpost. He is pursuing an integrated dual degree in Materials at the Indian Institute of Technology, Kharagpur. Nikhil is an AI/ML enthusiast who is always researching applications in fields like biomaterials and biomedical science. With a strong background in Material Science, he is exploring new advancements and creating opportunities to contribute.Nikhilhttps://www.marktechpost.com/author/nikhil0980/Anthropic Releases a Comprehensive Guide to Building Coding Agents with Claude CodeNikhilhttps://www.marktechpost.com/author/nikhil0980/ByteDance Releases UI-TARS-1.5: An Open-Source Multimodal AI Agent Built upon a Powerful Vision-Language ModelNikhilhttps://www.marktechpost.com/author/nikhil0980/LLMs Can Think While Idle: Researchers from Letta and UC Berkeley Introduce ‘Sleep-Time Compute’ to Slash Inference Costs and Boost Accuracy Without Sacrificing LatencyNikhilhttps://www.marktechpost.com/author/nikhil0980/OpenAI Releases a Practical Guide to Building LLM Agents for Real-World Applications

How to Instantly Explain Your Code with Visuals (Powered by GPT-4) 0 like April 22, 2025 Share this post Author(s): Mukundan Sankar Originally published on Towards AI. Tired of people not reading your blog or GitHub README? Here’s how to turn your Python script into a visual story anyone can understand in seconds. In Part 1, I introduced Code to Story — a tool that helps you turn raw Python code into a structured, human-readable story. I built it for one reason: I was tired of writing code I couldn’t explain. Not because I didn’t understand it. But because when someone — a hiring manager, a teammate, even a friend — asked, “What does this do?” …I froze. I’d stumble. I’d default to low-energy phrases like: “Oh, it’s just something I was playing around with…” I realized I had spent hours solving a real problem… only to fail at the most important step: communication. So I built a tool that solved that — something that turns code into a narrative. That was Part 1. But there was a deeper layer I hadn’t solved yet. Even after turning code into blog posts, people still didn’t engage. Why? Because they didn’t have the time. When I sent my blog to: Future hiring managersFriends I respectDevelopers I admire …they didn’t react. Not because they didn’t care. But because they were busy. Busy working. Job-hunting. Parenting. Resting. The truth hit me hard: No one owes your work their time. But you can make your work easier to understand in less time. So I asked myself: What’s the fastest way for someone to “get it” without reading anything? And the… Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI Towards AI - Medium Share this post

The GeForce RTX 4090 is a generation older than the new Blackwell 50 series GPUs, but this doesn't change the fact that it's still one of the most powerful cards out there, eclipsing the GeForce RTX 5080 or RTX 4080 Super or the Radeon RX 9070 XT or RX 7900 XTX. Only one GPU performs better - the RTX 5090 - and you'll need to use up a lifetime of luck to find one that isn't marked up by hundreds, even thousands of dollars.Because the RTX 4090 has been discontinued, it's getting harder to source as well. Fortunately, Dell still sells a Alienware Aurora R16 gaming PC configuration that can be equipped with a 4090 GPU. Not only is it one of the few RTX 4090 prebuilts still available - Lenovo and HP no longer carry them - it's also one of the more reasonably priced ones.Alienware Aurora R16 RTX 4090 Gaming PC for $2,999.99Alienware Aurora R16 Intel Core Ultra 7 265F RTX 4090 Gaming PC$2,999.99 at AlienwareThis Alienware Aurora R16 gaming PC is equipped with an Intel Core Ultra 7 265F CPU, GeForce RTX 4090 GPU, 16GB of DDR5-5200MHz RAM, and a 1TB NVMe SSD. The processor can also be upgraded up to an Intel Core Ultra 9 285K. If you're getting system with a focus on gaming, then the upgrade is unnecessary. Gaming at higher resolutions is almost always GPU bound, and besides, the default Intel Core Ultra 7 265F is a solid processor with a max turbo frequency of 5.3GHz and a total of 20 cores. It's cooled by a robust 240mm all-in-one liquid cooler and the entire system is powered by an 1,000W 80PLUS Platinum power supply.Get an Upgraded Model for $3,749.99Alienware Aurora R16 Intel Core Ultra 9 285K RTX 4090 Gaming PC (32GB/2TB)$3,749.99 at DellDell also offers this upgraded RTX 4090 model for $3,749.99 with free shipping. It's about $750 more than the base model Alienware 4090 gaming PC, but that's because the processor has been upgraded to a much more powerful Intel Core Ultra 9 285K CPU. You also get double the RAM and storage.How does the RTX 4090 stack up against current cards?The RTX 4090 is the most powerful RTX 40 series GPU on the market. Compared to the new Blackwell cards, only the $2,000 MSRP RTX 5090 is superior in performance. This card will run every game comfortably at 4K resolution; you should be hitting 60+fps even with all settings turned to the max and ray tracing enabled, doubly so if DLSS is supported. The only setting that the 4090 (as well as every other GPU) struggles with is path tracing, but no one really ever turns this on except during benchmark tests or social media flexing. The RTX 5090 might be faster, but for the vast majority of people out there, it's just wasted power since the 4090 already excels at pretty much all things gaming.Nvidia GeForce RTX 4090 GPU Review by Chris Coke"The RTX 4090 may be huge and expensive, but holy smokes if it doesn’t blow the competition out of the water. That’s a little unfair because it’s currently the only card of this new generation that’s available, so we only have cards from the past few years to compare it to. But until the rest of the pack can catch up, between its impressive hardware specs and its DLSS 3 AI wizardry, even the $1,599 price doesn’t seem unreasonable for the unrivaled frame rates that this card can crank out."Alternative: Alienware RTX 5080 Gaming PC for $2,400Alienware Aurora R16 Intel Core Ultra 7 265F RTX 5080 Gaming PC (16GB/1TB)$2,399.99 at AlienwareDell is offering an Alienware Aurora R16 gaming PC equipped with the new GeForce RTX 5080 GPU for $2,399.99 shipped. The RTX 5080 is one of three new Blackwell graphics cards that are out (and impossible to find). In our Nvidia GeForce RTX 5080 FE review, Jackie writes that "If you already have a high-end graphics card from the last couple of years, the Nvidia GeForce RTX 5080 doesn’t make a lot of sense – it just doesn’t have much of a performance lead over the RTX 4080, though the extra frames from DLSS 4 Multi-Frame Generation do make things look better in games that support it. However, for gamers with an older graphics card who want a significant performance boost, the RTX 5080 absolutely provides – doubly so if you’re comfortable with Nvidia’s AI goodies."Check out more of the best Alienware deals.Why Should You Trust IGN's Deals Team?IGN's deals team has a combined 30+ years of experience finding the best discounts in gaming, tech, and just about every other category. We don't try to trick our readers into buying things they don't need at prices that aren't worth buying something at. Our ultimate goal is to surface the best possible deals from brands we trust and our editorial team has personal experience with. You can check out our deals standards here for more information on our process, or keep up with the latest deals we find on IGN's Deals account on Twitter.Eric Song is the IGN commerce manager in charge of finding the best gaming and tech deals every day. When Eric isn't hunting for deals for other people at work, he's hunting for deals for himself during his free time.

If you're an anime fan, Crunchyroll is the best streaming platform out there. With just one subscription, you can instantly gain access to over 1,000 different anime series. In a time when anime has never been more popular, Crunchyroll allows you to catch new and popular shows like Solo Leveling while also keeping up with the biggest anime in the world like One Piece. Check out our full rundown of Crunchyroll as of April 2025, in addition to a free trial that allows you to try out the service for one week. Does Crunchyroll Have a Free Trial?7 Days FreeCrunchyroll Free TrialSee how to activate your free trial of Crunchyroll Premium.See it at CrunchyrollYes, Crunchyroll does offer a free streaming service trial. When you are ready to sign up for a plan, you can head over to the Crunchyroll Premium page and score a free seven-day trial on any of the three premium subscription options. This includes the Fan, Mega Fan, and Ultimate Fan tiers. Once your one week free trial ends, your subscription will automatically begin for the monthly price of your plan.What Is Crunchyroll? The Anime Streaming Service, ExplainedCrunchyroll is the biggest name in anime streaming, originally launching in 2006. You can find some of the most popular anime available like Attack on Titan, Dragon Ball, My Hero Academia, and more. The streaming platform was acquired by Sony through Funimation in 2020 for $1.2B, with Sony opting to sunset the Funimation streaming service as a result and folding it into Crunchyroll.The service is available for free with ads on select series and episodes, but Crunchyroll has slowly rolled back the number of anime you can watch without a Premium subscription. Just recently, almost all episodes of One Piece were made exclusive to Premium members only.How Much Does Crunchyroll Cost?Each Crunchyroll Premium tier is priced $4 apart. The Fan tier is set at $7.99/month, the Mega Fan tier is $11.99/month, and the Ultimate Fan tier is set at $15.99/month. The last time Crunchyroll increased prices was in May 2024, with only the Mega Fan and Ultimate Fan tiers affected.Crunchyroll PremiumChoose from the Fan, Mega Fan, and Ultimate Fan tiers.See it at CrunchyrollWhat Crunchyroll Premium Tiers Are There?Once again, Crunchyroll has three different pricing options for Premium members: Fan, Mega Fan, and Ultimate Fan. All anime is available across each of the tiers, so you won't need to worry about missing out on certain series if you do not subscribe to the highest tier.Fan Subscription - $7.99 per monthTo break down the tiers, Fan is the standard Crunchyroll Premium membership, offering the entire Crunchyroll anime library ad-free. You can actively stream on one device at a time, and you'll also recieve a 5% discount off select products at the Crunchyroll Store.Mega Fan - $11.99 per monthMega Fan is the most popular tier, with support for up to four different streams concurrently. This tier also unlocks offline viewing, so you can download episodes of any anime and watch them even if you do not have access to the internet. Mega Fan also gives you the Crunchyroll Game Vault, a selection of free games you can download to your mobile device. You'll also recieve a 10% discount at the Crunchyroll Store, up from the Fan tier's 5% discount, with free shipping on orders over $50.Ultimate Fan - $15.99 per monthFinally, Ultimate Fan is the last tier Crunchyroll offers. All perks from the Mega Fan plan carry over, except you can now stream on up to six different devices at a time. Additionally, your Crunchyroll Store discount is moved to 15%, with early access to deals like Manga Madness and free US shipping on orders. Lastly, active subscribers will receive an exclusive swag bag after 12 consecutive months of subscription.What's New on Crunchyroll - Spring 2025 SimulcastsPlayOne of the best features of Crunchyroll's Premium Tier is same-day simulcasts. New anime episodes that otherwise air exclusively on local Japanese stations promptly make their way to Crunchyroll for global audiences. While some of these simulcasts are available for free, the vast majority of new releases are behind that Premium paywall. So, what's airing now? The Spring 2025 anime season just kicked off, with ongoing simulcasts of My Hero Academia: Vigilantes, a new spin-off to the original series. The most recent My Hero Academia movie, You're Next, also just landed on the service. Other anime airing right now include Fire Force Season 3, Anne Shirley, The Beginning After the End, and One Piece, which just came back from a six-month hiatus. You can check out the full release calendar on the Crunchyroll site. How to Watch Crunchyroll - Available PlatformsCrunchyroll is available on almost every platform out there. You can watch anime on the official website, or on your mobile device with official apps for iOS, Android, Amazon Fire, and Samsung Galaxy. Additionally, the streaming service is available on gaming consoles like Nintendo Switch, PlayStation 5, and Xbox Series X|S. You can also use any media player like Apple TV, Google TV, Roku TV, and more to access the service.For more streaming platform guides, check out 2025 Hulu Subscriptions, Netflix Plans, ESPN+ Plans, and Disney+ Plans.

What iPhone 17 model are you most excited to see? [Poll]

iOS 18.5 public beta 2 has just been released, bringing the latest iPhone software version to members of Apple’s public beta program. Here’s what to expect. No additional features discovered in iOS 18.5 public beta 2 Yesterday, Apple shipped a new iOS 18.5 beta for developers, and today a fresh public beta has followed. Both releases are identical software builds, but Apple typically provides developers the first look to ensure no critical bugs make it into the update. Now, after a day of developer testing, public betas users have access to the latest version of iOS 18.5 too. No new features have yet been discovered in the latest beta. Instead, Apple appears focused on providing bug fixes and performance enhancements. As a result, the latest iOS 18.5 beta should run smoother on your iPhone than last week’s initial public beta. However, as is true with all beta software, your experience may differ from that of other users. It’s not uncommon for some users to encounter minimal bugs while other run into serious issues. As a result, if you’re not yet running the public beta, you may want to stay on iOS 18.4.1 for now. New features in iOS 18.5 so far are minimal—limited to two updates to Apple’s Mail app, and small UI changes in Settings. How has iOS 18.5 been running for you so far? Let us know in the comments. Best iPhone accessories Add 9to5Mac to your Google News feed.  FTC: We use income earning auto affiliate links. More.You’re reading 9to5Mac — experts who break news about Apple and its surrounding ecosystem, day after day. Be sure to check out our homepage for all the latest news, and follow 9to5Mac on Twitter, Facebook, and LinkedIn to stay in the loop. Don’t know where to start? Check out our exclusive stories, reviews, how-tos, and subscribe to our YouTube channel

Tesla has released its first-quarter earnings — and the numbers are even more brutal than we expected.The embattled carmaker missed analysts' expectations by a mile, reporting that its net income had slid an astonishing 71 percent since the first quarter of last year.The company's total revenue is down nine percent compared to the same period last year. Its car business in particular has felt the pain, with revenue falling 20 percent as buyers increasingly look elsewhere in the face of constant controversy.The key figure responsible for the trouble is the company's CEO Elon Musk, who has been widely criticized for dragging the EV maker's brand through the mud with his extremist views and disastrous slashing of government budgets with the help of his so-called Department of Government Efficiency after contributing hundreds of millions of dollars to Donald Trump's reelection efforts.Growing anti-Musk sentiment has spawned an entire "Tesla Takedown" movement, with countless protesters showing up at showrooms across the country.Sales have fallen off a cliff across the globe, with longtime Tesla bull and Wedbush Securities analyst Dan Ives warning that Musk had created a "code red" situation for the company.Earlier this month, Tesla revealed that the number of vehicles it delivered dropped by 13 percent in the first quarter of this year over the same period last year.Investors have voiced concerns over the mercurial CEO abandoning his carmaker in favor of gutting government agencies."Musk needs to leave the government, take a major step back on DOGE, and get back to being CEO of Tesla full-time," Ives argued in a Sunday note to clients. "Tesla is Musk and Musk is Tesla... and anyone that thinks the brand damage Musk has inflicted is not a real thing, spend some time speaking to car buyers in the US, Europe, and Asia."Complicating matters even further is Trump's trade war. A 25 percent tariff on auto imports could prove disastrous for Tesla. As the Wall Street Journal reports, Tesla relies on affected countries, including Mexico, for its auto parts.In a shareholder deck, Tesla confirmed that the trade war was hurting it. The company warned investors that "uncertainty in the automotive and energy markets continues to increase as rapidly evolving trade policy adversely impacts the global supply chain and cost structure of Tesla and our peers."One area where it is making modest revenue: carbon credits it receives from other automakers, who paid it $595 million to offset the CO2 pollution from their gas vehicles.In short, Tesla is in a bad state right now. Its share price is down well over 50 percent since hitting an all-time high shortly after Trump was elected late last year.And the company isn't promising smoother waters ahead this year, writing only that it will "revisit our 2025 guidance in our Q2 update."Share This Article

This is bonkers, even for Trump. Cell DwellerThe Trump administration is slapping giant tariffs on Southeast Asian-made solar panels — and the figures are so high, you may straight up gasp.As CNN and other outlets report, the United States is seeking tariffs of up to 3,521 percent — yes, you read that right — on solar cells and panels from Cambodia, Thailand, Malaysia, and Vietnam, all of which supply Chinese companies that have been accused of unfair competition.Nominally issued to help American companies compete against Chinese companies that flood American markets with cheap solar panels, the levies probably better serve to illustrate how far this president is willing to go in his trade war — even at the expense of cheap renewable power.Solar PainJust under a year ago, several solar panel companies petitioned then-president Joe Biden to instate tariffs on Chinese solar cell companies that had allegedly "dumped" their unfairly cheap products onto US markets and, in doing so, harmed American companies.Led by Hanwha Qcells, a South Korean company with facilities in the state of Georgia, and the Arizona-based First Solar Inc, the companies claim their Chinese counterparts are undercutting competition and harming their bottom lines when flooding American markets with uber-cheap products from Southeast Asia, some of which were priced below the cost of production.While it's not exactly clear why the Biden administration didn't take swifter action on those allegations, this seeming overcorrect under Donald Trump serves as a stark reminder of the state of play in his foolish trade war with China — and how starkly against clean energy this president remains.As the Houston Chronicle reports, renewable energy developers in the blood-red state of Texas have been plagued by uncertainty as their production timelines have been repeatedly stymied by the "wait-and-see" nature of Trump's tariffs."If this self-inflicted and unnecessary market uncertainty continues, we’ll almost certainly see more projects paused, more construction halted, and more job opportunities disappear," explained Michael Timberlake, the communications director for the clean energy group E2, in a statement.Share This Article

Max subscribers now have the option to add an “extra member” to their account for a smaller fee than the cost of a full-fledged separate subscription.According to the press release, this “Extra Member Add-On” feature “allows a primary account owner to share their Max account by inviting a friend or family member outside of their household to create a separate, standalone account with an adult profile under the same subscription.”It notes that extra members “will have their own login credentials separate from the primary account. Extra members can stream from one profile on one device at a time and can enjoy all other benefits included in the primary account owner’s base plan.”The price to add a person to your subscription is $7.99 a month — and the price is the same regardless of whether you’re subscribed to Max with or without ads. You can only add one “extra member” per account. Beyond that, anyone else will have to fend for themselves and subscribe at the full price.HBOHBOloading...READ MORE: Everything Coming to Max in May 2025Netflix recently added a similar option to add a person to an account who lives outside the member’s household. On Netflix, said extra person costs $6.99 per month for access with ads, or $8.99 per month to watch Netflix programming with no ads.As for whether it is worth all the trouble to add a person to your account (or, if you are the extra person, to beg your way onto a friend or loved one’s Max account), here are the current prices for an individual Max membership:Basic With Ads - $9.99 a month / $99.99 a yearStandard - $16.99 a month / $169.99 a yearPremium - $20.99 a month / $209.99 a yearIn other words: It’s cheaper, but the degree to which it’s cheaper is based on the tier. For two bucks more a month, you could have your own basic Max subscription (with ads), and you won’t have to worry about your dad guilting you about your mooching his streaming every time you talk on the phone.Get our free mobile appObscure Streaming TV Shows You Might Not Have Heard OfThere are so many streaming shows now. These are the ones you need to watch.Gallery Credit: Emma StefanskyFiled Under: Max, NetflixCategories: TV News